Distributed network with decentralised monolithic random number generation

Abstract

The present invention relates to a distributed network with decentralised monolithic random number generation, in particular a distributed network with decentralised monolithic random number generation with a high random bit data rate in order to ensure network security and robustness. The distributed network consists of a plurality of nodes, each node having a hardware-based quantum random number generator. Such a quantum random number generator comprises an entropy source fabricated monolithically in a semiconductor substrate, said entropy source comprising a photon source and a single-photon detector which are arranged perpendicularly to each other and to the surface of the semiconductor substrate in question, enabling a particularly high random number data rate. Each quantum random number generator comprises means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source. These quantum random number generators generate true random numbers decentrally with a high random bit rate without requiring a central node for generation or management. The random numbers are used to ensure the security, availability, and robustness of the network.

Description

[0001] Distributed network with decentralized one-piece random number generation

[0002] Subject of the invention

[0003] The present invention relates to a distributed network with decentralized single-piece random number generation, in particular to a distributed network with decentralized single-piece random number generation with high random bit data rate for ensuring network security and robustness.

[0004] A distributed network is proposed in which each node is equipped with a respective, preferably one-piece hardware-based quantum random number generator with a particularly high random bit rate. In today's interconnected world, the secure and reliable generation of random numbers is becoming increasingly important, especially in distributed networks where nodes lack a central control authority. In such networks, security often depends directly on the quality and unpredictability of the random numbers used for encryption, authentication, and other security-relevant operations. However, centralized quantum random number generators can represent an attractive target for attacks, which can lead to serious security vulnerabilities. These vulnerabilities are remedied by the present invention by decentralizing random number generation and distributing it among each node of the network.

[0005] Such a respective quantum random number generator of a respective node of such a network with distributed entropy generation preferably comprises an entropy source manufactured monolithically in a respective semiconductor substrate of the respective node (i.e., a network-suitable device at the respective node), which comprises a photon source and a single-photon detector arranged perpendicular to one another and to the surface of the respective semiconductor substrate, which enables a particularly high random number data rate. The respective quantum random number generator preferably comprises respective means for operating the respective entropy source and preferably respective means for generating quantum random numbers depending on the respective entropy source output signal of the entropy source.These quantum random number generators are characterized by this vertical arrangement of the photon source of the respective entropy source and the respective single-photon detector of the respective entropy source of the respective quantum random number generator within the semiconductor substrate of the quantum random number generator, ensuring that the generated random numbers are truly random, unpredictable, and of high entropy. Distributing these quantum random number generators across all nodes of the network creates a decentralized architecture that offers significant advantages in terms of the network's security, robustness, and scalability.

[0006] Preferably, the respective quantum random number generators are each constructed in one piece. Preferably, the respective semiconductor substrate of the respective quantum random number generator comprises a respective entropy source, which is fabricated in the respective semiconductor substrate of the respective quantum random number generator, and means for converting the entropy source signal of the entropy source into a random bit data stream. These means preferably comprise one or more of the following device parts: one or more analog amplifiers and / or filter circuits for conditioning the entropy output signal for subsequent analog-to-digital conversion; a single- or multi-bit analog-to-digital converter, which in the case of a single-bit analog-to-digital converter can be implemented by a comparator;one or more time-to-digital converters and / or one or more time-to-pseudo-random number converters for assigning a unique binary number to a time interval between two pulses of the entropy source; one or more entropy extraction devices for extracting one or more random bits from these binary numbers; one or more finite automata (so-called finite-state machines) for converting the data stream of random bits into random numbers; one or more interfaces for accessing these random numbers by one or more external computer systems and / or for controlling the quantum random number generator; one or more devices for carrying out and / or supporting a health check of one or more device parts and / or their interaction;one or more device parts for generating the internal operating voltages within the quantum random number generator for operating the various device parts of the quantum random number generator;

[0007] The respective quantum random number generators can preferably be an integrated quantum random number generator (iQRNG), in particular a monolithic, scalable and fully integrated photonic QRNG constructed in a common semiconductor substrate in the same material system, consisting of a photon source and a detector for individual photons directly coupled to the source in a particularly compact and attack-proof design on a technology platform for semiconductor structuring that is open for a wide range of applications.

[0008] The basic concept of the invention is that each node in a distributed network has its own hardware-based quantum random number generator, which operates independently and thus contributes to the overall entropy and security of the network. This leads to a significant increase in security, as there is no central component that could be compromised and compromise the entire network. Each node is capable of autonomously generating random numbers that can be used for a variety of security-relevant applications in the network, such as generating encryption keys, initialization vectors (IVs), one-time passwords (OTPs), and supporting security protocols such as TLS (Transport Layer Security) or IPsec (Internet Protocol Security).

[0009] Decentralized random number generation also makes the network more resilient to individual node failures, as its functionality isn't dependent on the availability or security of a central node. Even in the event of an attack or node failure, the other nodes in the network remain functional and capable of generating and using secure random numbers.

[0010] Another advantage of this decentralized structure is the scalability of the network. New nodes can be easily added, with each new node bringing its own source of random numbers. This allows for flexible and efficient network expansion without compromising performance or security. The burden of random number generation and other security-relevant processes is evenly distributed across the network, avoiding bottlenecks and performance degradation.

[0011] The invention also includes various error detection and recovery mechanisms that ensure the network is continuously monitored and reacts to anomalies in random number generation. Upon detection of problems, automatic recovery processes can be initiated to maintain the integrity and security of the network.

[0012] Overall, the present invention provides a robust and secure solution for the generation and use of random numbers in distributed networks. It addresses the weaknesses of centralized random number generation systems and ensures that the integrity and security of the network are maintained even in dynamic and changing environments. The decentralized architecture, based on hardware-based quantum random number generators at each node, offers significant advantages in terms of security, robustness, and scalability, making this invention a groundbreaking solution for modern distributed networks.

[0013] Technological background

[0014] The secure and efficient generation of random numbers in distributed networks represents a key challenge in modern network technology. The importance of random numbers ranges from encryption to ensuring data authenticity and integrity. However, existing technologies suffer from various shortcomings that can lead to potential security risks, performance bottlenecks, and scaling issues.

[0015] Quantum random number generators

[0016] Random events and the determination of probabilities play a particularly prominent role in many areas of science and technology. For example, Monte Carlo simulations and secure encryption methods rely heavily on the generation of random numbers. A general distinction is made between so-called pseudo-random numbers and true random numbers. While the former are generated using deterministic formulas by pseudo-random number generators (PRNGs), and are therefore not absolutely random, non-deterministic random number generators (TRNGs) for generating true random numbers are generally based on real, unpredictable processes such as thermal or atmospheric noise, rather than on artificially generated patterns by deterministic algorithms.However, even the results of such non-deterministic random number generators based on external parameters can, depending on the underlying random element, still tend slightly towards higher or even numbers due to weak correlations, for example, and thus enable at least a partial predictability of the random numbers generated in this way.

[0017] Quantum random number generators (QRNGs), a special subgroup of TRNGs, are based on fundamental quantum processes for random number generation and are therefore, at least theoretically, not dependent on other external factors and effects that influence statistics. Quantum random number generators thus represent the currently best available source of true random numbers. Current digital QNRGs can deliver entropy rates (i.e., a sequence of bit values ​​with maximum randomness or entropy) of up to several hundred Mbps. The generated random numbers are required in both classical encryption methods and a variety of quantum computing and quantum cryptography methods to ensure secure key exchange (Secure / Quantum Key Distribution, SKD / QKD).Therefore, non-manipulable and fast QRNGs are essential for generating secure keys in cryptography.

[0018] Due to their particularly easy implementation, many QRNGs are realized as photonic QRNGs using the random properties of photons. A simple concept for generating random numbers is the behavior of a photon, which is either reflected or transmitted at a semitransparent beam splitter independently of other photons. Another approach is to utilize the random arrival times of photons at a single-photon detector. This distribution effect, based on intrinsic, fundamentally non-deterministically computable photon statistics of the photons of a corresponding photon source, can also be used to generate truly random numbers with high entropy. The arrival times of photons at a single-photon detector generally exhibit an exponential distribution.

[0019] Typically, a single-photon detector (SPD) initially generates a detector pulse from a single incident photon. This pulse is then converted into a timestamped digital representation of the detection event in a time-to-digital converter (TDC) and can be further processed accordingly. The photon or entropy source in QRNGs is usually laser diodes (LDs) or simple light-emitting diodes (LEDs) that are highly attenuated to the single-photon level. Their emitted photons can then be recorded as SPDs with temporal resolution by one or more particularly sensitive single-photon avalanche diodes (SPADs).Such photon sources that simultaneously emit only a single photon or a few photons are also referred to as single-photon sources (SPS) in this application. However, they do not necessarily have to be true single-photon emitters, for example, based on a single isolated two-level system.

[0020] SPADs are a type of photodetector similar to photodiodes (PDs) and avalanche photodiodes (APDs), but with significantly increased sensitivity. SPADs can be digitally read and evaluated – even within a common integrated circuit. If such an integrated detector circuit is excited by individual photons, only one electron-hole pair is generated per exciting photon in the sensor-active region (absorption region). The excited electrons are drawn to the cathode by electric fields, and the excited holes are drawn to the anode. In a SPAD, the charge carriers drift through a so-called avalanche region, within which a charge avalanche is generated by enhanced impact ionization. These are therefore highly sensitive photon receiver elements that, upon activation, store a high amount of charge (approximately 105 - 10 6 electrons) with high temporal resolution.

[0021] A SPAD is typically operated in Geiger mode above its breakdown voltage, whereby a single photon is detected via the generated charge avalanche and subsequently registered as a single event. To reduce the dead time during registration, active or passive suppression or quenching of further charge carrier amplification can occur immediately after the onset of the avalanche formation. In addition to the SPAD, the integrated circuit can also include a so-called single-photon counter (SPC). In this case, instead of directly outputting a single detector pulse, an immediate statistical evaluation of the temporal distribution of the individual detected single-photon events is generally performed.

[0022] In the context of this application, the term quantum random number generator (QRNG) is primarily to be understood as an abstract definition in the sense of an arrangement for providing numerically measurable quantized random events. A quantum random number generator always comprises a so-called entropy source, i.e., an element that actually provides these random events (e.g., a PLC alone or in combination with an SPD). However, the term quantum random number generator is not limited to the entropy source, but can also encompass, for example, the environment and structural arrangement of the entropy source in a device or substrate. In general, however, this term also includes corresponding control and evaluation circuits or entire circuit layouts or logic components for actually outputting random events as directly processable random numbers.The random numbers can result directly from the statistics of the entropy source or, for example, through a conversion as random values ​​derived from it by additional measures. To better distinguish the abstract definition from a real circuit, the latter will also be referred to below as a quantum random number generator for the sake of simplicity. This is not intended to represent a restriction with regard to the two terms mentioned, but merely to highlight different aspects. In this respect, the terms quantum random number generator and quantum random number generator can also represent one and the same device (i.e., a quantum random number generator as a circuit element according to the general understanding), in which case both devices include at least one entropy source. In a circuit block diagram (i.e.At circuit level), a quantum random number generator according to the invention is therefore also referred to as an entropy source, while the circuit represented by the block diagram for outputting directly processable random numbers is referred to as a quantum random number generator for better differentiation.

[0023] In particular, the substrate of a quantum random number generator does not need to include any additional components to form a quantum random number generator. Instead, the substrate can, for example, be a single semiconductor crystal containing only one or more entropy sources. In this case, the additional components of a quantum random number generator can also be provided externally, for example, on another substrate.

[0024] Statistical analysis performed in parallel with random number generation can, for example, be used to further secure the random number generation process against potential attacks. Particularly in the case of non-integrated photonic QRNGs constructed from individual components, the required transmission paths within the system offer a wide range of attack possibilities. Therefore, to increase security, such systems are implemented as compactly and isolated from their external environment as possible. In addition to avoiding potential attack scenarios, a further advantage of such compact QRNGs is that natural influences from outside the system that may impair random number generation can also be largely minimized. Accordingly, compact QRNGs based on photon noise have typically been provided as hybrid integrated systems.

[0025] EP 3 529 694 B1 also discloses an integrated quantum random number generator (iQRNG) with a PLC and one or more SPDs, in which the PLC and the SPD(s) are fully integrated using CMOS technology in a single semiconductor substrate such that they are arranged directly adjacent to one another (see FIG. 1 with the associated figure description). The PLC is provided by an appropriately doped pn junction so that it generates a photon current to be detected when the photon source is suitably biased in the forward or reverse direction. The SPDs are said to be, in particular, SPADs, which are preferably produced by common manufacturing processes with the PLCs and have the same chemical structure.

[0026] The joint integration ensures that the photon flux generated by the SPS can flow directly to an adjacent SPAD through optical crosstalk within one and the same semiconductor material. Unlike other hybrid-integrated QRNGs known from the state of the art, it does not first have to overcome or tunnel through a possibly empty coupling gap that physically separates the two components. The integrated "side-by-side" configuration makes the QRNG presented in the publication more compact and structurally less complex than hybrid QRNGs of the same functional type. Furthermore, thanks to the integration of all components, the random number generator is significantly more robust and immune to external environmental influences as well as attempts at manipulation by external attackers.

[0027] However, it is still possible, at significantly increased expense, to interfere with, influence, and / or monitor the random number generation process during the QRNG's operation. Since the iQRNG disclosed in the publication essentially has a planar structure, individual photons could certainly be tapped or additionally introduced from above or below the plane of the substrate.

[0028] The horizontal juxtaposition of the structures is also not ideal in terms of efficiency and required space consumption. Efficiency is particularly limited by the required lateral distance between the SPS and the SPAD and the associated high absorption of the photons in the semiconductor material. Furthermore, without special precautions, the photons emitted by the SPS are largely scattered into the material surrounding the SPS, meaning that only a portion of the generated photons can be detected by an associated SPAD. While multiple SPADs can be arranged around a single SPS, increasing efficiency and thus the digital entropy rate through joint evaluation of the connected SPADs, this significantly increases the space consumption of such an iQRNG.On the other hand, even with a single emitter-detector pair, it must be ensured that undetectable photons cannot propagate uncontrollably within the substrate and cause interference elsewhere in the substrate. The associated lateral blocking regions therefore also increase the effective area consumption of the iQRNG.

[0029] An iQRNG, also realized in CMOS technology (HV-CMOS), with a corresponding arrangement of a photon source and a single-photon detector next to each other is also known from Khanmohammadi et al. (Khanmohammadi, Abbas, et al. “A monolithic silicon quantum random number generator based on measurement of photon detection time.” IEEE Photonics Journal 7.5 (2015): 1-13). An n-well located in a circular near-surface region between a central n ++The Si-LED, which acts as a photon source and is made up of a p++ region as the cathode and several p++ regions arranged in a ring around it as the anode, is enclosed in a circular ring by a SPAD as a single-photon detector (see FIG. 2 with the associated figure description). The photons emitted by the SPS are thus detected on all sides in the plane, which increases efficiency while requiring less space compared to the iQRNG known from EP 3 52 694 B1. The SPS is thus integrated directly into the SPAD. However, individual photons can also be emitted into the substrate or extracted from its surface. Likewise, the injection of corresponding photons by an attacker to influence the statistics is also possible in this way.

[0030] Therefore, to further increase security and reduce space consumption, there is a need for further miniaturization of integrated QRNGs compared to the state of the art. The iQRNG should be largely protected against external attacks while exhibiting the highest possible efficiency and the lowest possible substrate losses. To avoid being limited by manufacturing technology constraints in the design of SoCs (System on Chip, SoC), the underlying manufacturing process should be as technology-open as possible or based on the most widely applicable technology platform for semiconductor structuring. DE 10 2022 125 568 A1 relates to a data processing device comprising an integrated circuit containing a data processor and a non-volatile memory that stores at least one security code.A first memory external to the integrated circuit stores data, the data being cryptographically protected in a first format. A second memory external to the integrated circuit is used to store data. The device is arranged to transfer data from the first memory via the integrated circuit to the second memory so that the data processor can access it from the second memory. The integrated circuit is arranged to validate the data read from the first memory during transfer using a security code stored in the non-volatile memory. Once the data has been validated, cryptographic protection in a second format is applied to the validated data using a security code stored in the non-volatile memory. The protected data is stored in the second memory in the second format.The disclosure is directed to a computer comprising at least one quantum-process-based microintegrable generator for true random numbers as a random number generator with a high random bit output rate, particularly for encryption. Corresponding devices can also be found in DE 10 2022 125 569 A1, DE 10 2022 125 570 A1, DE 10 2022 125 571 A1, DE 10 2022 125 572 A1, DE 10 2022 125 573 A1, and the unpublished application with application number DE 10 2022 125 574.3.

[0031] Hardware-based centralized quantum random number generators

[0032] Previously known systems for random number generation in networks often use software-based random number generators and / or random numbers based on computer- and / or machine-implemented algorithms. These random number generators, also called pseudorandom number generators (PRNGs), are based on deterministic, computer- and / or machine-implemented algorithms that calculate random numbers in a predictable manner from an initial seed value. While these methods can be sufficient for many applications, they have significant weaknesses when it comes to highly secure applications. Because PRNGs are predictable due to their algorithmic nature, attackers who know or guess the seed value can predict the generated random numbers. This poses a significant security risk, especially in distributed networks where the integrity and security of communications are critical.Recently, Cl-based methods based on the well-known simple primitive feedback polynomials for linear feedback shift registers have attracted attention because they are able to estimate the feedback polynomial and the seed value used relatively quickly and thus break a large number of common encryption algorithms.

[0033] Another state-of-the-art approach is the use of hardware-based centralized quantum random number generators that exploit physical phenomena such as thermal noise or quantum effects. These approaches offer higher quality and unpredictability of the random numbers, but are often complex and expensive to implement when using state-of-the-art quantum random number generators. Some monolithic quantum random number generators have the disadvantage of relying on the generation of single photons that are transmitted laterally through a silicon substrate to a SPAD photon receiver. This has the disadvantage of low cross sections and high attenuation in a silicon semiconductor substrate.Only a fraction of the photons generated by the single-photon source in the silicon substrate are transmitted toward the single-photon detectors (here, SPAD photon receivers) by the single-photon source (preferably a SPAD or Zener diode) and are then massively attenuated in the silicon substrate, which is typically gray and opaque. This results in a low random number data rate in the current state of the art. Even the use of optical fibers in the metallization stack of the silicon semiconductor substrate only marginally improves this situation, since many of the photons from the single-photon source that emerge perpendicular to the surface of the silicon semiconductor substrate are reflected back by the metallization stack. Furthermore, the centralization of these systems poses a risk, as a single point of weakness in the system can compromise the entire network.

[0034] Decentralized security structure by avoiding a central node

[0035] In centralized networks where a single entity is responsible for generating and distributing random numbers, there is a risk of a single point of failure. If the central node is attacked or compromised, this can have serious repercussions for the security of the entire network. Such centralized systems are vulnerable to attacks in which attackers attempt to manipulate the central quantum random number generator or predict its output. These types of attacks can compromise all network communications and lead to significant security vulnerabilities. A central quantum random number generator must also provide a high random bit rate, which is technically extremely demanding and therefore vulnerable and error-prone.

[0036] Furthermore, centralization complicates network scalability. As the number of nodes increases, the central node can become a bottleneck because it must generate and distribute the centrally generated random numbers to all nodes. This leads to delays, increased latency, and potential performance degradation on the network. Managing and maintaining a centralized system can also be complex and costly, especially if the network is geographically distributed.

[0037] Use of random numbers for encryption

[0038] The security of encryption in networks depends crucially on the quality of the random numbers used. However, in the current state of the art, there are repeated cases where quantum random number generators lack sufficient entropy or exhibit systematic weaknesses, which compromise the security of the encryption. If the random numbers are predictable, encryption keys can be compromised, allowing attackers to decrypt encrypted communications and steal confidential information.

[0039] Another problem with using random numbers for encryption is the risk of random number reuse. Especially with PRNGs, it can happen that, after a longer runtime or if the generator is incorrectly initialized, identical random numbers are generated, resulting in weak or identical keys. This poses a significant security risk, as identical encryption keys can lead to identical ciphertexts that are easier to analyze and decrypt.

[0040] Support for security protocols

[0041] Security protocols such as TLS or IPsec rely on high-quality random numbers to establish secure communication channels between the nodes of a network. However, the state of the art often finds that the random numbers used for these protocols lack sufficient entropy or predictability, which can compromise the overall security of the protocol.

[0042] Another problem lies in the implementation and management of these protocols in distributed networks. Since many networks use centralized quantum random number generators, weaknesses or errors in the implementation of these protocols can become potential points of attack. Attackers could attempt to exploit vulnerabilities in random number generation to manipulate key exchanges or bypass authentication. This poses a significant threat to the integrity and confidentiality of communications on the network.

[0043] Random selection of nodes

[0044] In distributed networks, especially blockchain systems or other consensus-based networks, the random selection of nodes for specific tasks is crucial. However, the state of the art often finds that random selection algorithms are not completely random or are susceptible to manipulation. This leads to an uneven distribution of tasks and could allow malicious actors to manipulate the system by biasing the selection in favor of certain nodes.

[0045] Another problem is the lack of synchronization of random number generation across the network. In many systems, there is a risk that nodes do not generate random numbers uniformly, which can lead to predictable patterns. This poses a significant security risk because it allows attackers to target specific nodes or manipulate the distribution of tasks within the network.

[0046] Amplification and filtration of the entropy source

[0047] The current state of the art uses various methods to generate random numbers through physical processes. These entropy sources, such as thermal noise or quantum effects, are fundamentally capable of generating high-quality random numbers. However, there are also problems here: The generated entropy can be influenced by environmental conditions, leading to fluctuations in the quality of the random numbers.

[0048] Another problem is that many of the systems known in the prior art do not implement adequate mechanisms for amplifying and filtering the entropy source. This can result in the raw data from the entropy source not being sufficiently amplified or filtered before being converted into digital random numbers. This can introduce systematic errors or predictability into the generated random numbers, reducing their security and unpredictability.

[0049] Post-processing of random numbers

[0050] Most prior art random number generation systems rely on simple methods for processing the generated random numbers. These post-processing steps, such as hashing or XORing, are often used to further "improve" the random numbers. However, these methods often have weaknesses, especially if they are not implemented or configured correctly.

[0051] A well-known problem is that post-processing often cannot completely eliminate systematic errors. Especially when using simple algorithms, certain patterns can persist in the random numbers that can be exploited by attackers. This reduces the effectiveness of post-processing and compromises the security of the resulting random numbers.

[0052] Another problem is the potential reduction in entropy during post-processing. If the algorithms are not properly tuned, the initially high entropy of the random numbers can be reduced by inefficient or faulty post-processing steps, resulting in less secure random numbers.

[0053] Storage and access control

[0054] The secure storage of random numbers and other security-relevant data is another key issue in the state of the art. Many existing systems have significant security flaws in the storage of this data. Random numbers are often stored in insecure memory areas that are vulnerable to physical and logical attacks. This poses a significant risk, as unauthorized access to this data can compromise the overall security of the system. Another problem in the state of the art is inadequate access control to stored random numbers and security-relevant data. Often, the implemented access control mechanisms are not strict enough to prevent unauthorized access. This can lead to security vulnerabilities that allow attackers to access or manipulate sensitive data.

[0055] Network control and load balancing

[0056] Efficient control and load balancing in a distributed network represents another challenge in the state of the art. Many existing systems are unable to distribute the load evenly across the network, leading to bottlenecks and performance degradation. Particularly in networks with centralized quantum random number generators, overloads at the central node frequently occur, impacting the overall performance of the network.

[0057] Another problem is the lack of flexibility in load balancing. Many systems use static or simple round-robin strategies that cannot respond to current network load. This leads to inefficient resource utilization and can limit network scalability. In dynamic networks that rely on flexible and efficient load balancing, such limitations can impact the performance and reliability of the entire system.

[0058] Error detection and recovery

[0059] The current state of the art presents significant weaknesses in error detection and recovery in distributed networks. Many systems have limited or no mechanisms for continuously monitoring random number generation and overall network security. This leads to errors or anomalies often being discovered late, which can compromise the security and integrity of the network.

[0060] Furthermore, existing recovery processes are often not sufficiently automated or fast enough to respond to detected problems. This can lead to extended downtime or a complete network collapse. These deficiencies pose a significant risk, particularly in safety-critical applications where the continuous availability and integrity of random number generation are crucial.

[0061] Description of the invention

[0062] The object of the invention is achieved by the subject matter of the independent patent claims. Preferred developments are the subject matter of the dependent claims.

[0063] The present invention relates to a distributed network in which each node has a hardware-based quantum random number generator.

[0064] In particular, a distributed network according to the invention comprises a plurality of nodes, wherein each node of the plurality of nodes has at least one hardware-based quantum random number generator with at least one entropy source. The quantum random number generator at each node can be configured to generate truly random numbers (i.e., the quantum random number generator is a TRNG, as opposed to a PRNG). The network and / or sub-devices of the network can be configured to use the random numbers, in particular to ensure (i.e., within the framework of) the security, availability, and robustness of the network. The network and / or sub-networks of the network and / or sub-devices of the network can be configured to perform the random number generation in a decentralized manner, such that no central node is required to generate or manage random numbers.

[0065] A quantum random number generator may comprise an entropy source. It is preferred that the entropy source be monolithically embodied in a semiconductor substrate having a surface. The entropy source may comprise a photon source configured to emit photons (preferably single photons) when appropriately energized. Furthermore, the entropy source may comprise a single-photon detector configured to detect the photons from the photon source and generate an entropy source output signal. Preferably, the photon source is arranged between the surface of a semiconductor substrate in which the photon source is formed (this may be the same semiconductor substrate in which the entropy source is monolithically embodied) and the single-photon detector.Alternatively, the single-photon detector can also be arranged between the surface of a semiconductor substrate in which the photon source is formed (this can be the same semiconductor substrate in which the entropy source is monolithically formed) and the single-photon source. In other words, the respective entropy source of a respective quantum random number generator can have a respective vertical integration of the respective photon source and the respective single-photon detector of the respective entropy source perpendicular to the respective surface of the respective semiconductor substrate in which the respective single-photon source and the respective single-photon detector of the respective quantum random number generator are jointly fabricated.

[0066] It is particularly preferred for the photon source and the single-photon detector to be arranged vertically one above the other, e.g., when they are combined as hybrid structures, each with its own substrate, or, in the case of an entropy source monolithically integrated into a semiconductor substrate, to form a vertical stacked structure. The quantum random number generator can have a means for generating one or more quantum random numbers as a function of the entropy source output signal. A quantum random number can, for example, comprise a single quantum random bit or a quantum random data word composed of several quantum random bits. In particular, the quantum random number generator can be a quantum random (number) generator as described by way of example in FIG. 8, wherein the entropy source is preferably designed as described above.

[0067] Preferably, at least two, preferably all, nodes of the plurality of nodes of the network are configured to use the random numbers generated by their respective quantum random number generator and / or another quantum random number generator in the network to generate cryptographic keys and initialization vectors (IVs).

[0068] Preferably, at least two, preferably all, nodes of the plurality of nodes of the network are configured to use their respective random numbers and / or the random numbers of other nodes in the network to generate one-time passwords, OTPs, for the authentication of communication partners.

[0069] Preferably, the network or at least two, preferably all, nodes of the plurality of nodes of the network are configured to use their respective random numbers and / or the random numbers of other nodes in the network and / or random numbers in the network to support secure communication protocols such as TLS or IPsec.

[0070] Preferably, the network or at least two, preferably all, nodes of the plurality of nodes of the network are configured to use their respective random numbers and / or the random numbers of other nodes in the network and / or random numbers in the network to implement security protocols that preferably ensure secure communication between the nodes.

[0071] Preferably, the network or at least two, preferably all, nodes of the plurality of nodes of the network are configured to amplify and filter each random number generated by them by an entropy collection unit in order to preferably avoid systematic errors or predictabilities.

[0072] Preferably, the network or at least two, preferably all, nodes of the plurality of nodes of the network are configured to generate their respective random numbers by utilizing physical phenomena such as thermal noise and / or quantum processes.

[0073] Preferably, the network is configured so that the load of random number generation is distributed evenly across the nodes.

[0074] Preferably, at least two, preferably all, nodes of the plurality of nodes of the network each comprise a security module configured to securely store the random numbers of the respective node and to use and / or keep them available for one or more different security-relevant applications.

[0075] Preferably, at least two, preferably all, nodes of the plurality of nodes of the network each comprise a control device configured to store the random numbers in a protected memory area of ​​the control device of the respective node, which can only be accessed by authorized processes in the network.

[0076] Preferably, the respective control devices are configured to detect anomalies in the random number generation and to carry out corresponding recovery processes.

[0077] Preferably, the respective control devices are configured to subject the generated random numbers to post-processing in order to preferably improve their quality by techniques such as hashing or XOR-ing.

[0078] Preferably, the respective control devices are configured to use the random numbers to manage and use digital certificates required for authentication and establishing secure connections.

[0079] Preferably, the network has computer and / or machine-implemented mechanisms for error detection and recovery to ensure the functionality of the network even in the event of failure of individual nodes and / or failure of individual quantum random generators, for example by exchanging random numbers.

[0080] Preferably, the network is configured to prevent the use of unauthenticated vehicle or spare parts and / or software components by performing an authentication process upon installation or commissioning of such parts or components, which is based on random numbers generated by the hardware-based quantum random number generators in the nodes of the network.

[0081] Preferably, the authentication process comprises the generation of a cryptographic key by a node's quantum random number generator, which is then used to verify a digital certificate confirming the authenticity and integrity of the part or software component to be installed.

[0082] Preferably, the network is configured to detect the compromise of one or more nodes by implementing an Intrusion Detection System (IDS) that continuously monitors random numbers from the nodes' hardware-based quantum random number generators and identifies statistical anomalies in the random number generation that indicate (or may or could indicate) a compromise.

[0083] Preferably, the IDS performs a continuous entropy analysis of the random numbers generated by the quantum random number generators and sends an alarm message to a central control node in the vehicle network if deviations from expected entropy values ​​are detected.

[0084] Preferably, different cryptographic keys and / or encryption methods are used for communication between different pairs of nodes of the network, which are dynamically selected and generated by the random numbers generated by the quantum random number generators, preferably to increase the security of the communication.

[0085] Preferably, each node of the network is configured to use a unique combination of encryption methods and keys for each communication, which differs from the combinations of other pairs of nodes, preferably to prevent the compromise of one node from endangering the entire network.

[0086] Preferably, the network is configured to initiate defensive behavior of one or more nodes when a compromise of one or more nodes is detected, by the affected nodes disconnecting from communication in the network and reinitializing their quantum random number generators for an additional security check.

[0087] Preferably, the defensive behavior provides the affected nodes with the possibility of performing a self-test in which the integrity of the internal cryptographic keys and the random numbers generated by the quantum random number generator are checked before the node is allowed to communicate with the network again.

[0088] Preferably, the random numbers of the quantum random number generators will be used to generate one-time passwords (OTPs), which are required to access safety-critical functions of the vehicle, such as the activation of control units or the activation of firmware updates.

[0089] Preferably, the network is configured so that upon detection of a potential threat from a compromise of a node or group of nodes, a redundant network protocol is activated that reroutes the communication paths within the network and secures the communication by dynamically generating new random numbers for encryption and authentication.

[0090] The respective hardware-based quantum random number generator preferably has the features described in the following section "1. Hardware-based quantum random number generators at each node," in particular the features of its entropy source. These quantum random number generators are preferably integrated into each node of the relevant subnetwork and serve the decentralized generation of random numbers that can be used for a variety of security-relevant applications within the network.

[0091] 1 . Hardware-based at each node

[0092] Each node in the network is equipped with a hardware-based quantum random number generator.

[0093] Such a respective quantum random number generator can comprise an entropy source monolithically fabricated in a semiconductor substrate, comprising a single-photon source and a single-photon detector arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate. The respective quantum random number generator can comprise means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source. These quantum random number generators are characterized by precisely this vertical arrangement of the single-photon source and the respective single-photon detector of the respective quantum random number generator relative to each other in the semiconductor substrate of the quantum random number generator, which ensures that the generated random numbers are truly random, unpredictable, and of high entropy.By distributing these quantum random number generators across all nodes of the network, a decentralized architecture is created that offers significant advantages in terms of the security, robustness and scalability of the network.

[0094] Preferably, the respective quantum random number generators are each constructed in one piece. Preferably, the respective semiconductor substrate of the respective quantum random number generator comprises a respective entropy source, which is fabricated in the respective semiconductor substrate, and means for converting the entropy source signal from the entropy source into a random bit data stream. These means preferably comprise one or more of the following device parts: one or more analog amplifiers and / or filter circuits for conditioning the entropy output signal for subsequent analog-to-digital conversion; a single- or multi-bit analog-to-digital converter, which in the case of a single-bit analog-to-digital converter can be implemented by a comparator;one or more time-to-digital converters and / or one or more time-to-pseudo-random number converters for assigning a unique binary number to a time interval between two pulses of the entropy source; one or more entropy extraction devices for extracting the entropy of one or more random bits from these binary numbers; one or more finite state machines for converting the data stream of random bits into random numbers; one or more interfaces for accessing these random numbers by one or more external computer systems and / or for controlling the quantum random number generator; one or more devices for performing and / or supporting a health check of one or more device parts and / or their interaction;One or more device components for generating the internal operating voltages within the quantum random number generator to operate the various device components of the quantum random number generator. These characteristics, which characterize the quantum random number generator, could, for example, relate to certain physical processes, the type of entropy source, or specific circuit designs. The integration of such a respective quantum random number generator in each node enables true and non-deterministic random number generation, which is essential for secure network operations.

[0095] Variant 1 (not claimed):

[0096] The random number generator can be based on thermal noise, a well-known method for generating truly random numbers. Using this technology offers the advantage of being well-researched and proven, ensuring high reliability and reproducibility. However, such generators can be susceptible to environmental conditions such as temperature changes, which can be challenging in certain scenarios.

[0097] Variant 2:

[0098] Another variant claimed here according to the invention is the use of quantum processes for independent random number generation in each node. Quantum-based generators offer the potential for extremely high entropy and absolute unpredictability. However, the disadvantage so far has been that such systems were often more expensive and complex to implement, limiting their applicability in cost-sensitive environments. The technical teaching presented here solves this problem. According to the invention, such a quantum random number generator preferably comprises an entropy source fabricated monolithically in a semiconductor substrate, which comprises a single-photon source and a single-photon detector, which in turn are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate.The respective quantum random number generator comprises means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source.

[0099] Variant 3:

[0100] A combination of different physical phenomena can be used with variant 2 to generate the random numbers. This increases the complexity of the system, but offers the advantage of increased robustness against external influences, as weaknesses of one method can be compensated by the strengths of another. 2. Decentralized security structure through a central node

[0101] Decentralized random number generation in a network offers significant advantages over a centralized system where all random numbers are generated by a single node. In such a decentralized system, each node contributes to the overall entropy of the network, reducing the risk of an attack on a single component.

[0102] Variant 1 :

[0103] In a network with a fully decentralized architecture, there is no central control authority, which increases security because no single point can compromise the entire network. This variant offers maximum redundancy and resilience, but requires more complex management and synchronization of nodes to ensure consistency and synchronization.

[0104] Variant 2:

[0105] A semi-decentralized variant could involve a few nodes in the network taking on an expanded role in managing or distributing random numbers. These nodes could act as hubs, exerting some control over random number generation in neighboring nodes. This reduces the complexity of the network and facilitates management, but increases the risk of security issues if one of these hubs is compromised.

[0106] Variant 3:

[0107] Another option could be the implementation of a hybrid system in which a central authority exists but only assumes a monitoring and coordination role, without generating random numbers itself. This combines the advantages of centralized administration with the security of decentralized random number generation, but brings with it the challenge of making such a system secure and efficient.

[0108] 3. Use of random numbers for encryption

[0109] The random numbers generated by the quantum random number generators can be used to generate encryption keys and initialization vectors (IVs), which are necessary for secure communication between the network nodes. Variant 1:

[0110] The random numbers are used directly to generate symmetric encryption keys. This method is efficient and enables fast encryption and decryption of data, as symmetric key algorithms such as AES (Advanced Encryption Standard) require less computing power. The disadvantage, however, is that symmetric keys must be renewed regularly to maintain security.

[0111] Variant 2:

[0112] Alternatively, the random numbers could be used to generate asymmetric key pairs used in public key infrastructures (PKIs). This approach offers the advantage of increased security and scalability, as key distribution can be carried out securely over insecure channels. The disadvantage is the higher computational intensity and the longer time required for the encryption and decryption processes.

[0113] Variant 3:

[0114] Another possibility is to use the random numbers to generate initialization vectors, which are used in block encryption schemes such as CBC (Cipher Block Chaining). This variant increases security by ensuring that identical plaintext blocks generate different ciphertexts, making them more difficult for attackers to analyze. The disadvantage is the additional complexity in implementing and managing IVs.

[0115] 4. Support for security protocols

[0116] The decentralized random numbers can be used to support security protocols such as TLS (Transport Layer Security) or IPsec (Internet Protocol Security), which are necessary for secure communication between the nodes of the network.

[0117] Variant 1 :

[0118] The random numbers could be used directly for session initialization in TLS protocols. This enables secure negotiation of encryption keys and authentication information between the communication partners. The advantage of this variant lies in the proven security of TLS, but the disadvantage is the complexity of the protocol implementation and the necessary overhead.

[0119] Variant 2:

[0120] Another variant is the use of random numbers for authentication and key exchange in IPsec protocols. IPsec offers strong security at the network level and is particularly suitable for VPNs (Virtual Private Networks). The disadvantage of this variant is the potentially higher configuration effort and the possible impact on network performance due to the additional security measures.

[0121] Variant 3:

[0122] A hybrid solution could involve implementing both TLS and IPsec and using the random numbers to support both protocols. This offers maximum flexibility and security, but comes with increased implementation and maintenance effort.

[0123] 5. Random selection of nodes

[0124] In a distributed network, it may be necessary to randomly select nodes for certain tasks, such as validating transactions in a blockchain network. Decentralized random numbers can be used to ensure fair and tamper-proof node selection.

[0125] Variant 1 :

[0126] The random numbers could be used to randomly select nodes in a consensus-based network such as a blockchain. This ensures that no party can influence the selection, increasing the security and fairness of the system. However, the downside of this approach could be the increased complexity and the need for precise synchronization between nodes.

[0127] Variant 2:

[0128] Another variation is the random selection of nodes for tasks such as data replication or load balancing across the network. This can help distribute the load evenly and avoid bottlenecks. The advantage of this method is increased efficiency and flexibility, while the disadvantage is that uneven selection of nodes can lead to suboptimal performance parameters.

[0129] Variant 3:

[0130] Another application could be the random selection of nodes for performing security checks or audits on the network. This ensures independent and unpredictable verification of network security. However, the disadvantage could be that performing such checks creates additional overhead and places a strain on system resources.

[0131] 6. Amplification and filtration of the entropy source

[0132] The entropy collection unit in each node can be designed to amplify and filter physical signals before converting them into digital random numbers. This can be used to ensure the quality and unpredictability of the generated random numbers.

[0133] Variant 1 :

[0134] One variation could be the use of a highly sensitive amplifier capable of detecting and amplifying even the smallest fluctuations in the entropy source. This increases the accuracy and randomness of the generated numbers, but may be susceptible to environmental disturbances such as electromagnetic interference.

[0135] Variant 2:

[0136] Another option would be to implement a complex filter unit that only allows specific frequency ranges of the entropy source to pass through, eliminating noise and unwanted signals. The advantage of this method is that it increases the quality of the random numbers, while the disadvantage could be the additional computing power and the potential delay in random number generation.

[0137] Variant 3:

[0138] A combination of amplification and filtration could be used to both increase signal strength and reduce noise. This would increase the reliability and stability of the random numbers, but would increase the system complexity and implementation costs. 7. Post-processing of the random numbers

[0139] After the random numbers are generated by the hardware-based quantum random number generator, these numbers can be post-processed to eliminate systematic errors or predictabilities and further increase randomness.

[0140] Variant 1 :

[0141] A simple variant of post-processing could be applying a hashing algorithm such as SHA-256 to the generated random numbers. This would ensure that even small deviations in the input values ​​lead to significant changes in the output numbers, reducing predictability. The downside, however, could be the additional computation time required for hashing.

[0142] Variant 2:

[0143] Another variant could be XORing the generated random numbers with a predetermined random mask. This method is simple and fast, but may not offer the same level of security as more complex methods, as the predictability of the random numbers could persist under certain circumstances.

[0144] Variant 3:

[0145] A more complex variant would be to apply multiple post-processing steps, including hashing, XORing, and shuffling, to maximize the quality of the random numbers. This would ensure extremely high unpredictability and security, but at the expense of system performance and the required computational resources.

[0146] 8. Storage and access control

[0147] The generated random numbers and other security-relevant data can be stored in a secure storage area that is resistant to physical and logical attacks. Access to this data can be regulated through strict access controls to prevent unauthorized access.

[0148] Variant 1 :

[0149] One alternative could be the implementation of a hardware-based security module that stores the random numbers in an isolated memory area. This approach offers high security against physical attacks because the memory area is separated from the main processing unit. However, the disadvantage could be the increased complexity and associated cost.

[0150] Variant 2:

[0151] Alternatively, the random numbers could be stored in an encrypted memory area within the node's main memory. This method is less costly and easier to implement, but may offer less security against physical attacks because the main memory may be more easily accessible.

[0152] Variant 3:

[0153] Another option is to store the random numbers in a cloud-based secure storage protected by multi-factor authentication procedures. This option offers high flexibility and scalability, but introduces potential security risks due to external access and dependence on network latency.

[0154] 9. Network control and load balancing

[0155] The network can be designed to distribute the load of random number generation and other network resources evenly across the nodes. This can ensure that no nodes are overloaded and the network operates efficiently.

[0156] Variant 1 :

[0157] One variation could implement a simple round-robin load balancing strategy, where the random number generation tasks are distributed evenly among the nodes in a fixed order. This is easy to implement and ensures that the load is evenly distributed. However, the downside could be that inefficiencies arise if certain nodes are more heavily utilized than others.

[0158] Variant 2:

[0159] Another option could be dynamic load balancing based on the current node utilization. This involves distributing tasks based on real-time data on the current node utilization and availability. This ensures optimal use of network resources, but requires more complex algorithms and constant network monitoring. Option 3:

[0160] A hybrid strategy could be used, combining a basic round-robin strategy with dynamic adjustments when certain nodes become congested. This offers a balanced combination of simplicity and efficiency, but could be difficult to implement and maintain.

[0161] 10. Error detection and recovery

[0162] The network can have mechanisms for continuously monitoring for anomalies and perform automatic recovery processes when problems are detected. This can ensure that the network remains functional even if individual nodes fail and the integrity of random number generation is maintained.

[0163] Variant 1 :

[0164] A simple variant could be to conduct regular self-tests of the nodes to verify the functionality of the quantum random number generators. If anomalies are detected, the affected node could be automatically isolated and replaced. The disadvantage of this method could be that it does not react to errors in real time, and there may be some delay in error detection and correction.

[0165] Variant 2:

[0166] A more advanced approach could be the implementation of a real-time monitoring system that continuously monitors the performance and health of each node and initiates immediate recovery processes when a failure is detected. This would minimize response time and maximize network security, but requires a complex infrastructure and could result in increased operating costs.

[0167] Variant 3:

[0168] Another option is to implement a redundant system, where each node has a backup instance that is automatically activated in the event of a failure. This option offers high resilience but could significantly increase the cost and complexity of the network. Use of distributed networks in vehicles

[0169] The use of the aforementioned networks in vehicles is particularly advantageous. Vehicles are high-value assets that are constantly threatened by theft and other crimes. Therefore, the use of quantum-cryptographically secured networks is particularly advantageous.

[0170] 11. Prevention of the use of unauthenticated vehicle or spare parts and / or software components

[0171] The technical challenge here is to prevent the use of unauthenticated vehicle or spare parts and / or software components. This is particularly important in safety-critical vehicle applications, as the installation of uncertified parts or software can compromise the safety and integrity of the vehicle.

[0172] Variant 1 :

[0173] In a first variant, a digital authentication process can be initiated when a new vehicle part is installed. The network's random number generator generates a cryptographic key that is used to verify a digital certificate for the new part. The advantage of this method is its high security, as the random number generators generate high-quality keys that are difficult to tamper with. A disadvantage could be the increased computational load and the associated delay in the authentication process.

[0174] Variant 2:

[0175] A second variant implements a two-factor authentication process, using both a cryptographic key and a one-time generated password (OTP) to confirm the authenticity of the part or software. This further increases security by providing additional protection against unauthorized installation. The disadvantage of this method is that it requires a more complex infrastructure to support the OTP mechanism.

[0176] Advantage of a monolithically integrated quantum random number generator with a high random bit rate: A monolithically integrated quantum random number generator with a high random bit rate in each network node offers the advantage that authentication can be performed directly and decentrally using a large number of key bits. This increases the robustness of the system, as there is no dependence on a central random number generator, which could be a potential single point of failure. A central random number generator would be less advantageous, as it would limit the flexibility and scalability of the system and would be vulnerable to targeted attacks.

[0177] Interaction of the random number generators:

[0178] The monolithically integrated high-random bit rate quantum random number generators of the various network nodes preferentially cooperate by generating cryptographic keys and OTPs in parallel with a larger number of random bits as key bits for authentication. This decentralized generation of authentication data enables the network to respond flexibly to different authentication requirements and increases security by minimizing the attack surface and maximizing key security through increased key length.

[0179] 12. Secure verification of vehicle parts or software components during their installation or activation:

[0180] The technical problem is the secure verification of vehicle parts or software components during their installation or activation. Insecure verification could lead to the installation of counterfeit or compromised parts.

[0181] Variant 1 :

[0182] A first variant is the use of a digital certificate, where the certificate is verified by a cryptographic key with a high number of key bits based on random bits from one or more monolithically integrated high-speed quantum random number generators of one or more network nodes. Preferably, a monolithically integrated high-speed quantum random number generator of a network node generates this key to prevent attacks on the random number transfer between nodes. The advantage of this method lies in the fast and secure verification of parts that are immediately ready for use once validated. The disadvantage, however, could be the dependence on a digital certification infrastructure that requires regular maintenance.

[0183] Variant 2:

[0184] An alternative variant could involve multi-factor verification, where after the first certificate check, an additional check is performed by another node to confirm the integrity of the certificate. Preferably, this other node has contributed to the certificate with a second piece of certificate information based on one or more random numbers from a monolithically integrated high-speed quantum random number generator of this other node. Preferably, the first node has contributed to the certificate with a first piece of certificate information based on one or more random numbers from a monolithically integrated high-speed quantum random number generator of this first node. This double check based on monolithically integrated high-speed quantum random number generators further increases security but could lengthen the installation process.

[0185] Advantage of a monolithically integrated quantum random number generator with high random bit data rate

[0186] The use of a monolithically integrated high-speed quantum random number generator in each node enables fast and decentralized certificate verification without the need to send data to a central node for verification. This reduces latency and the risk of data interception. A centralized random number generator would slow down verification and pose an additional security risk, making it an attractive target for attacks.

[0187] Interaction of quantum random number generators with high random bit data rate

[0188] The nodes' respective controllers preferably cooperate using their respective monolithically integrated high-random-bit-rate quantum random number generators to perform redundant checks and ensure the authenticity of parts and software. This distributed security architecture prevents a single compromise from compromising the entire system.

[0189] 13. Detecting compromises within the vehicle network (intrusion detection) The technical problem is the detection of compromises within the vehicle network (intrusion detection). An undetected compromise could lead to the manipulation or misuse of vehicle functions.

[0190] Variant 1 :

[0191] One variant consists in the respective control devices of the respective nodes continuously monitoring the random numbers generated by the random number generator by means of an entropy analysis. For this purpose, the respective control devices preferably each have at least one said respective watchdog of the respective control device, which carries out this respective entropy analysis in the respective control device and generates one or more respective measures for the respective quality of the respective entropy of the respective random data stream generated in the respective quantum random number generator of the respective node of the network. The network can be configured such that it quantitatively calculates respective deviations in the expected respective entropy values ​​as respective entropy quality values ​​by comparing them with permitted entropy quality value ranges (e.g.in the form of one or more entropy quality values ​​exceeding these permissible entropy quality value ranges). Such deviations may indicate a compromise. There are various tests to determine the entropy of random numbers. A common approach is to calculate Shannon entropy, which quantifies the average information content per character of a source. A high entropy value indicates high unpredictability. The respective entropy quality value ranges can thus be defined by Shannon entropy values ​​(or by values ​​of another suitable entropy measure).

[0192] The advantage of this method lies in the early detection of threats, while the disadvantage lies in the computing power required for the constant analysis of random numbers. Therefore, it is advantageous if the CPU of the control device not only performs a computer-implemented method for entropy analysis and / or entropy evaluation, but can also rely on machine-implemented process components in the form of hardware acceleration devices as part of the respective control device of the respective network node. These are preferably part of the respective watchdog of the respective control device of the respective network node.

[0193] Variant 2:

[0194] Another variant provides that the respective control devices of the respective nodes of the network periodically perform respective computer-implemented and / or machine-implemented random number tests of the random numbers of the respective monolithically integrated high-data-rate quantum random number generators of the respective control devices of the respective nodes of the network and report the results to one or more predeterminable, programmable, or otherwise definable central nodes of the network. Preferably, the CPU of the control device of such a central node executes one or more computer- or machine-implemented methods for analyzing the data thus received and the respective suspicious deviations.The advantage of this method is the more or less centralized management and fast decision-making, while the disadvantage is the increased communication load and the dependence on the availability of one or more central nodes of the network.

[0195] Advantage of a monolithically integrated random number generator with high data rate in this context

[0196] A monolithically integrated, high-speed quantum random number generator in each node enables decentralized monitoring of random number generation, thus increasing the system's robustness against targeted attacks. A centralized random number generator would be more vulnerable to tampering and failure, which could compromise the overall security of the network.

[0197] Interaction of quantum random number generators

[0198] The monolithically integrated, high-data-rate quantum random number generators of the various nodes of the network preferably cooperate by continuously generating random numbers, which are checked for consistency and security by the CPUs of the control devices using computer- and / or machine-implemented methods. Deviations in the statistical distribution of the random numbers (e.g., variance or mean values, stuck-at errors, etc.) can be quickly detected by the CPUs of the control devices of the respective nodes, and measures can be taken to contain the threat before major damage occurs. To this end, the control devices of the network nodes preferably exchange generated random numbers with each other, check them, and report the verification results, preferably to the respective control device of the respective other node in the network.This allows other control devices at other nodes in the network to detect the compromise of a monolithically integrated high-rate quantum random number generator in another node and notify the remaining nodes in the network. The affected node can then enter an emergency mode, which may involve embedding random numbers from other monolithically integrated high-rate quantum random number generators at other nodes in the network.

[0199] 14. automated detection and response to the compromise of one or more nodes in the network

[0200] The technical challenge is the automated detection and response to the compromise of one or more nodes in the vehicle network. Without such mechanisms, a compromise could go undetected and lead to serious security problems.

[0201] Variant 1 :

[0202] In a first variant, control devices of nodes in the network can continuously perform an entropy analysis of the random numbers generated by their respective monolithically integrated high-data-rate quantum random number generators and, if necessary, also of the random numbers of the monolithically integrated high-data-rate quantum random number generators of other nodes in the network. Preferably, the control devices use their respective watchdogs, preferably present, for this purpose. The respective control device of a node in the network can, preferably in the event of anomalies detected by a computer- and / or machine-implemented method, preferably a statistical method, send an alarm message to the central control node. The advantage of this variant lies in the rapid detection and central coordination of the response, while the disadvantage lies in the potential overload of the central control node.

[0203] Variant 2:

[0204] An alternative variant could be for the alarm messages to be sent not to a central node, but to multiple control nodes by the respective control device of the respective node in the network. Typically, the CPUs of the control devices of these multiple control nodes then jointly decide on the next steps using respective computer- and / or machine-implemented processes, which preferably synchronize with each other and exchange signaling and / or data with each other. These then typically execute these steps as computer- and / or machine-implemented steps. This distributes the load and increases the system's resilience, but could increase the response time.

[0205] Advantage of a monolithically integrated quantum random number generator with high random bit data rate

[0206] A monolithically integrated quantum random number generator with a high random bit rate in each node enables detection and response to compromise to be carried out decentrally with very long keys and therefore with high security, increasing the efficiency and security of the system. A centralized random number generator would be a potential target for attacks, which could compromise the security of the entire network.

[0207] Interaction of the quantum random number generator with high random bit data rate:

[0208] The monolithically integrated quantum random number generators with high random bit rate independently generate high-quality and difficult-to-influence random numbers, which are continuously monitored, preferably by the aforementioned watchdogs of the control devices. If anomalies are detected, the affected nodes in the network can be isolated, and the generated random numbers can be used to support the restoration of an uncompromised network.

[0209] 15. Ensuring secure communication between the nodes of the network

[0210] The technical problem is to ensure secure communication between the nodes of the network by using different cryptographic keys and / or encryption methods for different pairs of nodes or groups of nodes.

[0211] Variant 1 :

[0212] In a first variant, a new, longer cryptographic key is generated for each new communication between two nodes by the monolithically integrated quantum random number generator with a high random bit rate of one of the participating nodes. The high random bit rate enables the use of long keys. The advantage of this method is the massively increased security, as each communication channel is unique, making it more difficult to track or decrypt by unauthorized third parties. The disadvantage could be the increased computational load resulting from the constant use of new keys. Ultimately, the data bus bandwidths of the communication channels between the nodes are reduced by the transmission of new keys for the next key exchange. However, this increases the rate between the number of key bits transmitted in the data channel divided by the number of useful bits transmitted in the communication channel.This reduces the likelihood of compromise because the key change occurs so quickly that an attacker has too few useful bits available to break the key.

[0213] Variant 2:

[0214] A second variant could be for the control devices of groups of nodes within the network to each use their own specific computer-implemented and / or machine-implemented encryption methods, which use random numbers from the respective monolithically integrated quantum random number generator with a high random bit rate of the control device of the respective node. Preferably, the monolithically integrated quantum random number generator with a high random bit rate of a node generates random numbers more or less permanently for this purpose. The respective control device of the respective node preferably periodically updates which of these respective random numbers the respective control device uses. This method offers the advantage of high security within node clusters but could increase the complexity of key management.

[0215] Advantage of a monolithically integrated quantum random number generator with high random bit rate

[0216] A monolithically integrated quantum random number generator with a high random bit rate, preferably in every node of the network, enables the keys required for encryption to be generated locally and in real time, without having to resort to central network resources and the risk of compromised communication. This reduces the vulnerability to attacks on central systems and increases the security of communication overall. A central random number generator would be a potential risk, as its compromise would endanger all communication channels.

[0217] Interaction of monolithically integrated quantum random number generators with high random bit data rate

[0218] The monolithically integrated high-speed quantum random number generators in the nodes each generate individual long keys and encryption methods using these long keys for each communication link. They also enable continuous key exchange. This ensures that communication between nodes is always individually secured with relatively new and long military-grade keys and reduces the possibility of attacks through key reuse or decryption to near zero. Because the monolithically integrated high-speed quantum random number generators generate truly random numbers, the likelihood of identical, previously used keys reappearing after a key exchange is extremely low, especially if they have a very long key.

[0219] 16. Avoiding security vulnerabilities through the use of repeated encryption methods or cryptographic keys within a network

[0220] The technical problem is to avoid security vulnerabilities caused by the use of repeated encryption methods or cryptographic keys within a network.

[0221] Variant 1 :

[0222] In one variant, all communication between control devices of the network nodes is secured by a combination of random numbers and a dynamic computer- and / or machine-implemented encryption method determined by the monolithically integrated quantum random number generators with a high random bit rate of the control devices of the participating nodes. For example, a control device can send the same data message to another control device multiple times at this node, encrypting the data message separately using different keys from different control devices at different nodes. This control device then sends these multiple differently encrypted data messages, possibly together with information regarding the respective key used, to the control device of the other node. The control device of the other node decrypts the data messages.If the contents of the various data messages do not match after decryption, at least one key generation and / or transmission is compromised. The transmission of the respective information about the respective key used is not absolutely necessary. Without this information, the receiving control device must try all available keys to decrypt an encrypted data message, which is time-consuming and quickly results in an NP-complex problem. This method prevents key reuse and significantly increases security. The disadvantage, as described, could be the increased computational complexity and the need for effective key management in the respective computer systems of the respective control devices of the respective nodes in the network.

[0223] Variant 2:

[0224] An alternative variant could be that each control device of each node in the network preferably has a fixed key set, randomly generated by the monolithically integrated quantum random number generators with a high random bit rate, which is regenerated at specific, preferably very short intervals by the respective monolithically integrated quantum random number generators with a high random bit rate of the respective control devices of the respective nodes. This method reduces the need for constant recalculations but could compromise security in the event of a node being compromised. However, it is particularly advantageous if the synchronization of the key sets is partially lost due to a high data transmission error rate or if an intrusion is detected.The control devices can then signal this to each other and switch to a non-compromised key.

[0225] Advantage of a monolithically integrated quantum random number generator with high random bit rate

[0226] A monolithically integrated quantum random number generator with a high random bit rate enables the local and continuous generation of new encryption methods and longer keys that are unique for each communication. This increases the security of the network by reducing the likelihood that an attacker can compromise the entire communication channel by decrypting a single message. A centralized random number generator would be disadvantageous here, as it could become a single point of failure.

[0227] Interaction of quantum random number generators with high random bit data rate

[0228] The monolithically integrated high-random-bit-rate quantum random number generators preferably work together by generating new, unique keys for each respective communication connection, thus ensuring that no keys are reused. This prevents security vulnerabilities and increases the integrity of the network.

[0229] 17. Development of a defensive behavior of the network

[0230] The technical problem is to develop a defensive network behavior that responds to the detection of compromises and maintains the integrity of the network.

[0231] Variant 1 :

[0232] In a first variant, the control device or the watchdog of the control device of the affected node can detect a compromise and initiate immediate measures, preferably to isolate itself from the network, while simultaneously performing random number generation using the control device's monolithically integrated high-random bit rate quantum random number generator of the affected node to verify its internal security mechanisms. The advantage of this method lies in its rapid response capability, while the disadvantage could be the temporary unavailability of the affected node.

[0233] Variant 2:

[0234] However, the effects of this can be prevented if the affected node, first, notifies other nodes in the network of its compromise using a preferred broadcast message and, second, if the corresponding node switches to a predefined emergency mode, based, for example, on a non-compromising program in a non-writable memory of its control device. An alternative variant therefore provides that the control device of the affected node, in addition to isolating itself, sends a warning to one or more or all of the remaining nodes in the network, causing them to also activate their internal random number generation and / or random number monitoring and / or random number verification processes to detect and prevent similar threats. This increases the security of the entire network but could lead to increased load on the nodes.

[0235] Advantage of a monolithically integrated quantum random number generator

[0236] A monolithically integrated quantum random number generator with a high random bit rate, preferably in every control device of every node in the network, enables the response to compromises to be carried out decentrally and autonomously within the network. This ensures that even if one node is attacked, the rest of the network remains secure. A centralized random number generator would not offer this flexibility and autonomy and, if compromised, would endanger the entire network.

[0237] Interaction of quantum random number generators

[0238] The controllers of the monolithically integrated quantum random number generators with a high random bit rate work together to enable immediate, autonomous responses to potential threats. This increases the resilience of the network and ensures that the system's integrity is maintained even in the face of attacks.

[0239] 18. Ensuring the functionality and integrity of a network

[0240] The technical problem is to ensure the functionality and integrity of a network, even if a node is temporarily unavailable or its functionality is impaired.

[0241] Variant 1 :

[0242] In one variant, after isolation, the control device of the affected node performs a complete self-test, preferably of all verifiable device components of the affected node, including analyzing the random number generation by the control device's monolithically integrated quantum random number generator. Furthermore, the control device checks the cryptographic key integrity. For example, the control device may have stored a key set a second time, albeit encrypted, in a specially secured memory of the control device for verification purposes. The advantage of this method lies in the thorough verification and restoration of the node's security, while the disadvantage could be the longer duration of the verification process.

[0243] Variant 2:

[0244] An alternative variant could be for the control device of the affected node to continue to communicate in a limited manner during the self-test, but only via differently secured secure channels and with minimal data. In this case, particularly sensitive data is preferably not sent or received. This method ensures a certain level of connectivity but could increase implementation complexity.

[0245] Advantage of a monolithically integrated quantum random number generator with high random bit rate

[0246] A monolithically integrated quantum random number generator with a high random bit rate enables fast and efficient verification of the node's security-critical functions without the need to access external resources. This increases the node's autonomy and security. A centralized random number generator could not fulfill this function, as it would not be capable of performing self-verification in a decentralized manner.

[0247] Interaction of quantum random number generators with a high random bit rate

[0248] The monolithically integrated quantum random number generators with a high random bit rate support the continuous verification and restoration of node integrity through autonomous generation and validation of random numbers, thus ensuring the security and functionality of the network even if a node is temporarily isolated.

[0249] 19. Secure management and use of safety-critical functions

[0250] The technical problem is the secure management and use of safety-critical functions in the vehicle by generating and managing very long one-time passwords (OTPs) with high randomness and high security against side channels using monolithically integrated quantum random number generators with a high random bit rate. This prevents unauthorized access to these safety-critical functions.

[0251] Variant 1 :

[0252] In one variant, the monolithically integrated quantum random number generators with a high random bit rate in the nodes' control devices generate very long and therefore very secure OTPs, which are required to access safety-critical functions such as starting the engine or deactivating safety devices. The advantage of this method is its high security, as each OTP can only be used once, is difficult to reproduce, and is very long and extremely random. The disadvantage could be the need for constant synchronization between the nodes to correctly manage the OTPs. This reduces the effective data rate in the network. Variant 2:

[0253] An alternative approach could be to have the OTPs generated using monolithically integrated quantum random number generators with a high random bit rate be valid for a limited time only and automatically replaced by new OTPs if they are not used within this timeframe. This further increases security but could lead to problems if the OTPs are not synchronized in a timely manner. For this purpose, encrypted software sets would be useful.

[0254] Advantage of a monolithically integrated quantum random number generator

[0255] A monolithically integrated quantum random number generator with a high random bit rate in a control device of a network node enables the fast and secure generation of longer and thus more secure OTPs directly in the control device of the respective node, without any dependence on central systems. This increases the security and flexibility of the system. A central random number generator would be less suitable here, as it could reduce the security and availability of the OTPs if it were compromised or overloaded.

[0256] Interaction of quantum random number generators

[0257] The control devices, with their monolithically integrated high-random bit rate quantum random number generators in the network's nodes, work together to ensure that OTPs are synchronized and securely distributed between the nodes. This ensures that only authorized users have access to security-critical functions and that these functions are protected from unauthorized access.

[0258] 20. Ensuring communication and functionality of the network

[0259] The technical problem is that even when a potential threat or compromise of one or more nodes is detected.

[0260] Variant 1 :

[0261] In one variant, the control device of the affected node can detect a potential threat and switch to a preferably computer- and / or machine-implemented minimalist mode of operation of the control device of the affected node, in which preferably only safety-critical functions of the affected node remain active in an emergency state, particularly in the form of a predefined, computer- and / or machine-implemented emergency operation procedure, and communication by the control device of the node is reduced to the necessary minimum. The advantage of this method is the rapid response and the preservation of safety functions, while the disadvantage could be the limited functionality of the node.

[0262] Variant 2:

[0263] An alternative approach could be for the affected node's controller to detect the threat and send a message to the other nodes, which would then tighten their security measures and possibly use alternative, preferably more secure, communication paths and / or methods to isolate the affected nodes. This approach increases network security but could result in increased load on the remaining nodes.

[0264] Advantage of a monolithically integrated quantum random number generator

[0265] A monolithically integrated quantum random number generator with a high random bit rate enables the control device of each node to respond quickly and securely to threats by protecting security-critical functions and maintaining communication within the network. A centralized random number generator could not ensure this rapid response and would be more vulnerable to attacks.

[0266] Interaction of quantum random number generators

[0267] The node controllers, with their monolithically integrated high-speed quantum random number generators, work together to ensure that network security and communication are maintained even in the face of threats. This increases the network's resilience and protects it from attacks or failures.

[0268] The preceding explanations demonstrate the flexibility and adaptability of a decentralized vehicle network equipped with monolithically integrated quantum random number generators with a high random bit rate. These monolithically integrated quantum random number generators with a high random bit rate not only provide high quality and security in the generation of cryptographic keys and random numbers, but also enable flexible adaptation to different security requirements and rapid response to threats. The decentralized structure of the network and the close cooperation of the node control devices with the monolithically integrated quantum random number generators with a high random bit rate minimize the attack surface and maximize the security and resilience of the network.The variants described illustrate how the specific technical problems are solved and what advantages such a network offers for use in vehicles.

[0269] A further aspect of the present disclosure relates to the respective node-specific integrated quantum random number generators, wherein the entropy source can preferably comprise an integrated quantum random number generator, iQRNG, as described according to the invention. The terms quantum random number generator and quantum random number generator are used essentially synonymously. The entropy source of such an integrated quantum random number generator of a network node according to the invention of a subnetwork according to the invention of a network according to the invention preferably comprises a photon source and a single-photon detector, wherein the photon source and the single-photon detector are arranged vertically one above the other in a common substrate made of a semiconductor material. An entropy source of an iQRNG according to the invention can also comprise a plurality of photon sources (e.g.to increase the photon rate or reliability) or multiple single-photon detectors coupled to a single photon source (e.g., for monitoring purposes). An iQRNG according to the invention can comprise one or more such entropy sources. It is also possible to combine multiple photon sources and single-photon detectors into an entropy source of a single iQRNG.

[0270] In particular, the quantum random number generator can therefore preferably comprise an integrated quantum random number generator (iQRNG) as an entropy source, in particular a monolithic, scalable, and fully integrated photonic QRNG constructed in a common semiconductor substrate in the same material system, consisting of a photon source and a detector for individual photons directly coupled to the source, in a particularly compact and attack-proof design on a technology platform for semiconductor structuring that is open to a wide range of applications. According to the invention, the nodes of a subnetwork according to the invention of the network according to the invention have one or more such quantum random number generators (iQRNGs) connected to one another for data purposes via data lines.

[0271] An integrated quantum random number generator, iQRNG, can comprise a photon source and a single-photon detector, wherein the photon source and the single-photon detector are arranged vertically one above the other in a common substrate made of a semiconductor material. "Vertical stacking" means that the photon source and the single-photon detector are stacked at different depths relative to a surface of the substrate (a side-by-side arrangement would then be horizontal, for example). "Vertical stacking" preferably means that the propagation direction of the photons transmitted between the photon source and the single-photon detector has at least one component in said vertical direction.The photon source and the single-photon detector may therefore also have a mutual lateral offset or a tilt of the active regions with respect to the surface of the substrate, as long as photons emitted by the photon source can be detected by the single-photon detector with at least one propagation component in said vertical direction. It is particularly preferred if the propagation of the photons essentially (i.e., in a ray-optical approximation without diffraction effects) has only one component in said vertical direction (i.e., no horizontal component). An iQRNG according to the invention may also comprise multiple photon sources coupled to a single single-photon detector (e.g., to increase the photon rate or reliability) or multiple single-photon detectors coupled to a single photon source (e.g., for monitoring purposes).It is also possible to combine several photon sources and single-photon detectors into a single iQRNG.

[0272] In contrast to the state of the art, the entropy source of the iQRNG does not feature a juxtaposition of the individual optoelectronic components. Instead, a compact arrangement of a photon source and a single-photon detector is to be arranged one above the other in a common substrate made of a semiconductor material. The semiconductor material is preferably silicon. The use of direct semiconductors such as GaAs or combination semiconductors made of I II / V semiconductor materials or even more complex semiconductor materials that can be produced by band-gap engineering is conceivable. This thus represents a particularly compact monolithic 3D integration with minimal space requirements for the iQRNG, whereby the structures can preferably be formed in one piece.In particular, an arrangement is preferred in which the at least one single-photon detector of the one or more single-photon detectors is arranged lower than at least one photon source of the one or more photon sources in the respective semiconductor material (i.e. photon source on top, single-photon detector below) for improved shielding against external influences. In an alternative embodiment, however, the exemplary single-photon detector in question can also be arranged higher than the respective photon source in the semiconductor material (i.e. photon source below, single-photon detector above). For example, in addition to an inversion of the basic structural design during processing from the surface of the substrate (in particular semiconductor substrate), an inverse arrangement of the elements can also be achieved by appropriate structuring from the back of the semiconductor substrate.In particular, structuring can be carried out on both sides, from the front side as well as from the back side of the semiconductor substrate.

[0273] The photon source is preferably a single-photon source (SPS), designed to provide only a single photon or a few photons at a time. Such photon sources that provide only a single photon or a few photons at a time are also referred to as single-photon sources in this application. However, they do not have to be true single-photon emitters, for example based on a single isolated two-level system; rather, conventional light sources can also be designed as SPSs by appropriately attenuating the emission or the supplied current. This is preferably a silicon LED or a PN junction in the semiconductor substrate, or a pip, pin, or nin structure in the semiconductor substrate, or a functionally equivalent semiconductor structure in the semiconductor substrate.

[0274] In the context of the present disclosure, a semiconductor substrate is understood to mean the entire semiconductor chip as a body in which a specific element structure is patterned into the semiconductor material, for example by means of CMOS, bipolar, BiCMOS, or other semiconductor process technologies, for example by forming differently doped wells or regions and / or oxidations and / or trench etching and / or undercutting. However, the structure can also be formed additively by applying structured and / or unstructured additional layers and structures or by a sequence of etching and application steps for such additional layers and structures. Such methods are well known from microstructure technology and from microelectronics manufacturing processes. The document presented here refers to the relevant specialist literature.A corresponding semiconductor substrate can therefore comprise, in addition to a so-called carrier or base substrate (e.g., an unstructured single-crystal semiconductor substrate as the basis for the epitaxial growth of further semiconductor layers), a plurality of such epitaxially grown layers as well as other coatings. The semiconductor substrate is therefore understood in this application as a material carrier for the semiconductor structures of an iQRNG according to the invention and not in the sense of a simple carrier or base substrate for applying these structures. In this respect, the integral formation of an iQRNG according to the invention, one above the other in a common substrate made of a semiconductor material, represents a distinction, in particular from hybrid integrated combinations using conventional methods (e.g.,by means of flip-chip assembly) consisting of at least one photon source and at least one single-photon detector, for example on a common submount as a carrier structure.

[0275] The photon source is preferably a light-emitting diode, preferably a PN diode, operated at an operating point below or close to the breakdown voltage. Particularly preferably, the photon source is a light-emitting avalanche Zener diode (Zener-avLED) operated at an operating point below or close to the breakdown voltage. The Zener-avLED preferably has a breakdown voltage of <10 V, more preferably a breakdown voltage of <8 V, and even more preferably a breakdown voltage of <7 V. This breakdown voltage can be very accurately adjusted using methods known from the prior art and precisely adjusted during the design phase using known component simulators by specifying the doping profiles and structures. The advantages of using a Zener-avLED as a single-photon source are explained in more detail below.This new type of single-photon source allows for a high single-photon rate at a relatively low operating voltage, even below and in the range of the Zener breakdown voltage. With the desired design, the generated photons are preferably emitted directed into the substrate interior and thus toward the single-photon detector. This makes Zener avLEDs particularly suitable for use as a single-photon source in an entropy source of a quantum random number generator (or an iQRNG). Preferably, the single-photon detector(s) are one or more single-photon avalanche diodes (SPADs). These are detectors that, due to their particularly high sensitivity with high amplification and low (dark) noise, are in principle capable of detecting and proving single photons.

[0276] A main idea of ​​the present invention is therefore to provide a particularly compact and secure integrated QRNG with a particularly compact and secure entropy source for each network node of said subnetwork of the proposed network by arranging a Zener avLED and a SPAD one above the other in a common semiconductor substrate, which enables a higher random number data rate than is usual in the prior art. As a result, the proposed network has the ability to generate random numbers with high quality and high security at a high data rate for the network as a whole. Thus, such a network, if it comprises a sufficient number of corresponding nodes with the proposed quantum random number generator, is superior to all networks with a central quantum random number generator and all networks with conventional iQRNGs.

[0277] One approach to improving the state-of-the-art iQRNG is to select a correspondingly broad technology platform. For SoC designs with the broadest possible range of potential applications, integrated circuits based on bipolar CMOS-DMOS (BCD) technology on silicon offer great potential. Highly efficient SPADs have already been successfully demonstrated and implemented using BCD technology. BCD technology allows for particularly effective and optimized integration of these SPADs with a wide range of other functional groups, such as digital and analog circuit components, particularly energy-efficient digital memory and switching elements, general power and driver electronics, and detector and sensor components.

[0278] The silicon-based PLCs known in the state of the art can, in principle, also be implemented in BCD technologies. However, due to the undirected emission of photons and their typically near-surface implementation, such Si LEDs are not optimal for the realization of particularly efficient and attack-protected iQRNGs. The near-surface implementation also usually results in degradation in the case of a Si LED used in avalanche operation. However, since silicon, as an indirect semiconductor, is poorly suited for photon generation, and these can generally only be generated through further processes via additional interaction with the crystal lattice, the selection of possible alternative silicon-based photon sources is severely limited.

[0279] In investigating Zener diodes provided in different layers by corresponding pn junctions in a BCD technology, which are optimized for a permanent operating point even in the breakdown region, with a near-surface Zener diode operating as an emitter and an underlying simple pn diode without bias (zero bias) operating as a detector, the inventors were able to demonstrate that, contrary to the general expectation of the skilled person, in this configuration, strong electroluminescence with an efficiency of at least 0.03% can be observed in the Zener diode in avalanche operation at the breakdown voltage. Such Zener diodes are not typically intended for operation as optoelectronic components (LEDs) in the prior art.

[0280] In particular, the generated photons are preferentially emitted toward the lower pn diode, which can thus detect almost all emitted photons, which can also be demonstrated via a photocurrent in the inventive structure (see FIGS. 4 to 7 with the associated figure description). It was thus shown that the investigated Zener diode exhibits a low but nevertheless significant efficiency in the range of the breakdown Zener voltage (approximately one detected photon per 3000 electrons of the Zener diode current) and therefore appears to be ideally suited as single-photon sources for the realization of QRNGs in silicon-based BCD technology. Above all, the preferential radiation toward the detector offers significant advantages over the isotropic radiation used in entropy sources of conventional iQRNGs.The silicide commonly used in CMOS technology to reduce contact resistance between the metal contacts and the semiconductor silicide is both light-tight and mirror-smooth, so that even photons originally emitted upwards can be reflected back into the substrate by the silicide mirror. Accordingly, Zener diodes designed in avalanche mode and operated as SPS are therefore referred to below as light-emitting avalanche Zener diodes (Avalanche Light Emitting Zener diodes, Zener-avLEDs), in contrast to the prior art Si-LEDs. The Zener-avLEDs provided in the BCD technology used here as an example emit photons with wavelengths from the visible spectral range and have a relatively low Zener operating voltage of usually less than 8 V.Since the emission of a Zener avLED is typically directed such that the photons are emitted preferentially in a vertical direction, i.e., away from the surface and into the substrate, a significantly stronger isolation of the SPS and the generated photons from the environment of the semiconductor material can be achieved when used in an iQRNG, and the tapping or injection of photons at the detector surface is significantly more difficult. With a suitable design of the SPAD belonging to an iQRNG, the efficiency of random number generation can also be significantly increased, and uncontrolled photon propagation in the semiconductor material can be largely prevented.

[0281] The second essential component for constructing a compact QRNG is therefore the selection of a suitably adapted SPAD design. Typically, these are also implemented near the surface in BCD technologies by appropriately forming p- or n-wells. Such near-surface SPADs are quite comparable to the prior art SPADs implemented in CMOS technology. In principle, the iQRNG known from EP 3 529 694 B1 with the Zener avLEDs described above could therefore also be implemented in BCD technologies. However, as already described above, the Zener avLEDs advantageously emit the photons preferably in the direction into the substrate. A juxtaposition of a Zener avLED as an SPS and a near-surface SPAD, as known from the prior art, could in principle be implemented, but not necessarily effectively.When using Zener avLEDs, it is advisable to place the corresponding SPAD below the Zener avLED.

[0282] In addition to the implementation of conventional n-SPADs and p-SPADs, BCD technology also enables the implementation of completely new SPAD concepts, including the use of deep n- or p-doped layers in a BCD substrate.

[0283] Using a method also recently developed by the inventors for generating deep pn junctions in a BCD process to provide a corresponding BCD substrate with deep pn junctions, a particularly efficient deep-lying single-photon avalanche diode ("deepSPAD") was realized. This deepSPAD can be easily arranged directly below a Zener avLED configured to generate single photons. The combination of a Zener avLED with a deep-lying SPAD thus provides the essential components of a QRNG that is fully vertically integrated using BCD technology, in contrast to the CMOS-based horizontal integration of a QNRG (or the entropy source of an iQRNG) according to the state of the art.

[0284] By vertically arranging a Zener avLED as the emitter and a deepSPAD as the receiver, realized using extremely deep pn junctions, a miniaturized quantum random number generator based on a monolithic silicon die with highly efficient optical coupling, high attack resistance, and low operating voltage can be realized using BCD technologies. The BCD-based iQRNG design presented here with the vertical entropy source thus represents an optimal solution for providing an iQRNG according to the invention. In particular, the vertical 3D integration can further increase the compactness of an iQRNG (or the entropy source of an iQRNG) and reduce the area consumption compared to conventional lateral 2D designs while simultaneously increasing efficiency.

[0285] Preferably, an iQRNG according to the invention (or an entropy source of an iQRNG) is therefore formed in a BCD substrate using BCD technology.

[0286] Preferably, the BCD substrate comprises a carrier substrate; and an epitaxial layer grown on the carrier substrate, wherein a deep pn junction located in the epitaxial layer is created between the carrier substrate and the epitaxial layer by diffusion of dopants introduced into a surface of the carrier substrate below the epitaxial layer.

[0287] The carrier substrate can preferably be a p-type substrate. However, n-type substrates or intrinsic substrates can also be used. The substrate material can in particular be silicon. However, the processes are in principle also adaptable for other semiconductor materials. A typical dopant for forming a p-type region is boron. Phosphorus (P), arsenic (As), or antimony (Sb) can be used to form an n-type region. In silicon, for example, boron as a dopant diffuses significantly further than the heavy donors (P, As, or Sb). It can also be seen that the n-type regions created are largely dominant due to the higher doses used, i.e. an n-type region already doped with phosphorus can retain its existing conductivity type even after additional boron has been added.To provide the deep pn junctions, additional mask, lithography and epitaxy steps in the usual BCD process can sometimes be omitted.

[0288] Preferably, the first and second dopant have different diffusion properties in the carrier substrate and / or in the epitaxial layer. Preferably, the second dopant has greater mobility in the carrier substrate and / or in the epitaxial layer than the first dopant. Preferably, the introduction of the first dopant and / or the second dopant takes place maskless or via a mask process. For maskless introduction, a direct ion beam writing process, for example, can be used. In a mask process, the introduction takes place with the aid of a previously provided mask, wherein the introduction takes place, for example, via a chemical or physical deposition process or likewise by means of an ion beam writing process.Preferably, immediately after the introduction of the second dopant, the first region or the second region completely overlies the other region in a plan view of the surface of the carrier substrate. Preferably, the first region is a deep n-type layer (NBL layer) and the second region is a deep p-type layer (PBL layer).

[0289] Preferably, the single-photon detector forms an avalanche region in a region around the deep pn junction and comprises an absorption region for converting photons into electron-hole pairs, wherein the absorption region is directly adjacent to the deep pn junction.

[0290] It is preferred that the deep pn junction is formed at least partially between a deep n-layer as the cathode and a deep p-layer directly adjacent to the deep n-layer. It is also preferred that the absorption region directly adjoins the deep p-layer and is essentially formed as a p-region. Essentially means that the absorption region can also be partially formed as an intrinsic region. It is further preferred that a + -area formed anode is directly adjacent to the absorption area.

[0291] Preferably, a second deep pn junction formed below the deep pn junction of the single-photon detector located in the epitaxial layer (e.g., in the carrier substrate) is used as an additional photodetector for monitoring for external attacks. The aforementioned method for generating deep pn junctions in a BCD process results in a second pn junction located below the first pn junction in some embodiments (see FIG. 3 with the associated figure description). Due to its largely identical electronic properties, this second pn junction can also be configured as a photodetector or single-photon avalanche diode. Since this additional photodetector is thus arranged below the actual QRNG arrangement, buried deep in the semiconductor material, it can provide a protective function against photons injected from the back of the substrate.These can be detected in close proximity to the QRNG over a wide angular range. This allows external attacks to be detected with a high degree of probability.

[0292] Furthermore, the additional photodetector can be configured to enable monitoring of the photon count rate via additional evaluation electronics. Under otherwise constant operating conditions, the photon source and the associated single-photon detector should exhibit a roughly constant photon count rate, apart from random statistical fluctuations in the detected photon events. However, since not all photons emitted by the photon source may be detected by the associated single-photon detector, and external natural influences (e.g., cosmic rays) and artificial radiation (e.g., radio sources) can also cause isolated detection events at the additional photodetector, the second photodetector will, with a certain probability, also exhibit a roughly constant background count rate.Deviations from this long-term statistical average can therefore indicate a possible error within the iQRNG or external interference, such as from an attacker. A detected change in the background count rate at the second photodetector can indicate both active interventions by an attacker (e.g., irradiation of additional photons to change or influence the photon statistics) and passive attacks, such as the targeted thinning of a shield to increase the transmission of individual photons to the outside (which may, however, also cause additional irradiation of ambient light from this direction).

[0293] Since background count rates are also statistical variables, an analysis based on machine learning methods is recommended for evaluating possible deviations from expected normal values. Artificial intelligence methods can be used for the evaluation. In particular, the use of at least one appropriately trained artificial neural network (ANN) is preferred for detecting an attack and / or identifying possible error sources and events. A variety of different types of ANNs can be found in the literature; the expert can select suitable methods based on the specific requirements.

[0294] In some embodiments, the at least one ANN may comprise a stochastic neural network (SNN), which can provide variable outputs for the same photon count rates. This allows for the investigation of network errors based on the available data or insufficient training of the network. For example, it can also identify deviations that are not represented by the deviation space of a training data set (out-of-distribution).

[0295] Another possible application of the deep second pn junction as an additional photodetector can be the provision of independent random numbers based on another independent photon source located below the deep second pn junction or on or near the back of the substrate. For this purpose, the deep second pn junction is preferably also configured as a single-photon detector or SPAD, analogous to the deep first pn junction located above it.Since the absorption of photons in the region of the first single-photon detector can also be subject to a probability distribution and, depending on the specific realization of the arrangement of the individual elements, individual photons from the actual photon source of the iQRNG according to the invention can also reach the region of the deep-lying second pn junction, it is also possible that these can also be used as a basis for providing quantum random numbers, for example as an additional independent iQRNG.

[0296] Regardless of the use of a deep second pn junction as an additional photodetector, an iQRNG according to the invention (or a corresponding quantum random generator) can also comprise a further photodetector that is independent of the described deep pn junctions. Preferably, the further photodetector is also integrated into the iQRNG according to the invention, but it can also be connected to the iQRNG according to the invention in a hybrid manner. Particularly preferably, the further photodetector is also a single-photon detector, e.g., a SPAD. Analogous to the use of the deep second pn junction described above, the additional photodetector can also be used to monitor the functionality and safety of an iQRNG according to the invention.Preferably, the deep-lying first pn junction and the deep-lying second pn junction are connected to one another via a common internal terminal, for example a common anode or cathode. Typically, pn junctions configured for operation as single-photon detectors are connected directly via the substrate on one side of the pn junction. However, due to the shielding or isolation of the structures and circuits from the substrate, which is common practice, particularly in BCD technologies, corresponding terminals for contacting are often placed on the substrate surface. However, with a design of a pn junction double structure according to the invention, a common terminal region (anode or cathode) is immediately created, which enables joint control via a single contact, e.g. on the substrate surface.

[0297] Preferably, the top and / or bottom of the substrate in the region of the iQRNG (or the entropy source of the iQRNG) is mirrored on one surface or comprises a light-blocking layer. Mirroring the surfaces of a substrate (e.g., by means of metallization or the application of dichroic layers) and the application of a light-blocking layer are known in the art and have already been discussed above. These approaches can also be used in an iQRNG according to the invention to shield against external photons ("shadowing") and to increase efficiency by reflecting back the photons generated by the associated photon source. Alternatively or additionally, appropriate encapsulation can also be provided in the region of the iQRNG or to surround this region with a metal box.

[0298] Preferably, the surface of the substrate is covered with a silicide layer in the region of the iQRNG (or the entropy source of the iQRNG) and with a metallization layer above it. Preferably, the metallization is closed in the region of the iQRNG. The metallization can act as a mirror coating for the interior and / or as a wavelength-independent shading for external photons. The same applies to a formed silicide layer.

[0299] Preferably, the escape of photons provided by the photon or single-photon source at the surface of the substrate and / or the back of the substrate is prevented by a combination of at least one element each consisting of metal covers, sidewall contacts, and vias. These elements can achieve a largely complete shielding or encapsulation of the iQRNG (or the iQRNG's entropy source), which not only provides external shielding but also ensures high immunity to external interference. However, with regard to possible attack scenarios, other external access methods are conceivable in addition to purely optical interference or the reading of emitted photons.A further aspect of the present invention therefore consists in further hardening an iQRNG according to the invention, which already offers significantly increased security compared to the prior art due to its specific arrangement of the included photon source and the associated single-photon detector, against unauthorized access and external influences, for example, by observers or attackers. Possible optical shielding has already been discussed above; further attacks could be carried out, for example, based on targeted evaluation or manipulation of chemical or electronic properties of the iQRNG according to the invention.

[0300] As mentioned at the beginning, quantum random number generators utilize the principles of quantum mechanics to generate truly random numbers that can be used in cryptography and other security-critical applications. These random numbers are crucial because they form the basis for secure encryption keys and other cryptographic processes. Despite their theoretical security, however, QRNGs can be vulnerable to various types of side-channel attacks that can compromise the integrity and confidentiality of the generated random numbers.

[0301] One possible attack vector is electromagnetic radiation. QRNGs can emit electromagnetic signals that can be intercepted and analyzed by an attacker. These signals could reveal information about the internal states of the QRNG, which could allow an attacker to reconstruct or predict the generated random numbers. To prevent such attacks, QRNGs should be well-shielded and protected against electromagnetic radiation.

[0302] Another attack vector is power consumption. The power consumption of a QRNG can vary depending on the random numbers generated. An attacker could measure these fluctuations and use them to draw conclusions about the generated random numbers. This could be achieved by using highly sensitive power meters capable of detecting even the smallest changes in power consumption. To prevent such attacks, QRNGs should be designed so that their power consumption remains constant regardless of the random numbers generated.

[0303] Temperature dependence can also play a role. The performance of QRNGs can be temperature-dependent, meaning that changes in the ambient temperature could affect random number generation. An attacker could manipulate the device's temperature to influence or predict the random numbers. To prevent such attacks, QRNGs can be operated in temperature-controlled environments and have mechanisms that keep their performance stable regardless of temperature fluctuations.

[0304] With optical QRNGs such as the iQRNG according to the invention, an attacker could also attempt to influence the light source or monitor the detectors to manipulate the generated random numbers. This could be done by introducing additional light or by blocking light. To prevent such attacks, optical QRNGs should be well shielded and protected against external influences.

[0305] There are also so-called timing attacks. By measuring the time a QRNG takes to generate random numbers, an attacker could identify patterns and predict the random numbers. This could be achieved by using high-precision timing devices capable of detecting even the smallest differences in generation time. To prevent such attacks, QRNGs should be designed so that their generation time remains constant regardless of the random numbers generated.

[0306] Chemical attacks on semiconductor-integrated QRNGs are a less researched but potentially serious risk. These attacks could, for example, aim to alter the physical properties of the semiconductor components in order to influence or disrupt random number generation.

[0307] One possible approach for chemical attacks is to alter the semiconductor materials through chemical reactions. This could be achieved through exposure to corrosive substances that compromise the integrity of the semiconductor structures. Such attacks could impair the performance of QRNGs by reducing the efficiency of the light sources or detectors or by altering the electrical properties of the circuits.

[0308] Another potential chemical attack could involve the targeted doping of semiconductor materials. By introducing foreign atoms into the semiconductor layer, an attacker could alter the electronic properties of the material and thus influence random number generation. This could lead to predictability of the generated random numbers, which would significantly compromise the security of the QRNGs.

[0309] Although chemical attacks on QRNGs are currently theoretical and not yet widespread in practice, these potential threats should be considered and measures should be taken to ensure the chemical stability and integrity of QRNGs. This can be achieved, for example, through the use of protective coatings, the selection of chemically resistant materials, and the implementation of monitoring mechanisms to detect chemical changes.

[0310] These potential attack scenarios demonstrate that even state-of-the-art QRNGs are not fully protected against side-channel attacks. It is therefore important to implement additional security measures to ensure the integrity and confidentiality of the generated random numbers. These include, among other things, physically shielding the devices, implementing mechanisms to stabilize power consumption and generation time, and operating in controlled environments.

[0311] In an iQRNG according to the invention, the aforementioned shielding can be achieved directly via the implemented structural system itself or the buried arrangement of the entropy source inside a substrate. Shielding against both electromagnetic and optical radiation can be achieved, for example, by a common and continuous metallization of the surface of the substrate above the entire build volume of the iQRNG (or the associated entropy source). Metallization can also be applied at the corresponding location on the underside of the substrate to shield the lower build volume. In addition to their shielding function, these individual metallizations can also simultaneously enable electrical contacting of individual areas of the iQRNG. Preferably, several metallization levels can be arranged one above the other to increase the layer thickness (e.g., 12-15 layers).

[0312] Metallic multilayers generally provide better shielding than a single metal layer. This is because multiple layers of different or identical metals can be combined to maximize the shielding effect. One reason for this is that each metal layer can reflect and absorb electromagnetic waves. Combining multiple layers increases the likelihood that the waves will be reflected and absorbed multiple times, improving overall shielding. Different metals have different shielding properties. More effective shielding can be achieved by combining metals with complementary properties. For example, a layer of a highly conductive metal such as copper could be combined with a layer of a ferromagnetic material such as nickel.Multiple layers can also help dampen the penetration effects that might occur with a single layer. This is especially important for high-frequency electromagnetic waves, which tend to penetrate thin metal layers. Multi-layer shielding also provides an additional layer of protection. If one layer becomes damaged or corroded, the other layers can continue to provide effective shielding.

[0313] Instead of one or more metal layers, a layer of polysilicon can also be applied to the surface of the substrate in the iQRNG area to shield against electromagnetic radiation (including photons). Polysilicon is frequently used in the semiconductor industry, particularly in the manufacture of transistors and solar cells. While it does not have the same shielding properties as metals and is also generally more optically transparent to photons at the same thickness, it is a more cost-effective process and significantly easier to implement.

[0314] Furthermore, a circuit or IC comprising the iQRNG according to the invention (or a region or part thereof) can be covered, in addition to the above-mentioned layers for shielding or as a single element, preferably with a layer of silicon nitride (SiN). Such a layer can keep a certain previously set hydrogen content (H2) in an IC as constant as possible, since SiN layers have only low permeability for this. A constant hydrogen content is important in the manufacture and operation of ICs for several reasons. First, hydrogen helps to avoid defects in semiconductor materials such as silicon. These defects can impair the electrical properties of the semiconductor components and lead to malfunctions. A constant hydrogen content minimizes such defects and ensures the reliability of the ICs.In addition, hydrogen is often used to passivate the surfaces of semiconductor materials. This means that hydrogen binds to the surface atoms, thus reducing the number of free electrons that could cause unwanted chemical reactions. A constant hydrogen concentration ensures that passivation remains effective. Hydrogen can also help reduce the oxidation of metal compounds in ICs. Oxidation can reduce the conductivity of metal compounds and thus impair IC performance. A constant hydrogen content helps control oxidation and maintain the conductivity of the metal compounds. Finally, fluctuations in the hydrogen content contribute to changes in the electrical properties of semiconductor materials. This can impair the performance and reliability of the ICs and also open up a vector for chemical attack.A constant hydrogen content helps to keep the electrical properties stable and ensure consistent performance.

[0315] The lateral region around the iQRNG or the enclosed entropy source can be created by appropriate deep doping of the substrate or by designing it as a conductive region. Such an arrangement can be used, analogous to metallization of the substrate surfaces, simultaneously for deep contacting of regions located within the substrate, such as for contacting buried layers. However, to avoid additional electromagnetic radiation from these structures, they are preferably not used to transmit modulated signals. In the exemplary embodiments of iQRNGs according to the invention shown in the figures, this shielding region can be seen as isolated outer deep structures extending vertically from the surface into the substrate.In a preferred embodiment of an iQRNG according to the invention, the "detector surface" of the single-photon detector is designed as a circular structure, so that the lateral shielding then preferably forms a closed circular-ring-shaped cylindrical structure (however, the shielding can have any shape, preferably one with a closed side). Such an arrangement of lateral shielding against electromagnetic radiation is also referred to as a so-called seal ring (iQRNG seal ring).

[0316] The insulating well regions typically formed in BCD technologies, here particularly around the photon source and the single-photon detector, can also be used for shielding. These are usually used to electrically isolate different regions in a substrate, so that, for example, different reference potentials (GND) can be provided in these regions. However, such local insulation also has a current-blocking effect for signal transmissions and, with a suitable design of the individual well regions, can also effectively suppress electromagnetic coupling between the isolated regions. As a further shielding element, the conventional encapsulation of an iQRNG according to the invention (or of an IC comprising one or more iQRNGs according to the invention) with a standard potting material such as plastic can be used. The plastic can in particular be duroplast.Silicon oxide (e.g. SiO2) can be added to the thermoset to adjust the thermal expansion coefficient of the materials joined together.

[0317] Preferably, several iQRNGs according to the invention or a multi-channel QRNG system comprising a plurality of iQRNGs according to the invention (e.g., with one or more entropy sources according to the invention) are implemented on the same substrate in order to increase the data rate of the quantum random bits. Together with compact shielding of the entropy source of the individual iQRNGs, very high integration densities can be achieved with a large number of one or more densely packed, and preferably decoupled, entropy sources of one or more iQRNGs, and thus overall high effective random number rates. With entropy sources of iQRNGs in the prior art, the integration density is primarily limited by the structural juxtaposition of the individual components.

[0318] Preferably, an iQRNG according to the invention comprises an electronic circuit for generating and outputting a digital random number sequence based on the statistical evaluation of the temporal sequence of signals (single-photon detector signals) of the one or more single-photon detectors.

[0319] A further aspect of the present invention relates to an integrated electronic circuit (IC) comprising at least one iQRNG according to the invention. In particular, these ICs can be used for applications based on security-relevant chip-based systems (SoCs).

[0320] Preferably, an iQRNG according to the invention (or the entropy source of the iQRNG) is placed in a pad frame (also referred to as the pad edge) of the integrated electronic circuit. Preferably, the electronic circuit for generating and outputting a digital random number sequence is also located in the pad frame. In non-pad-determined integrated electronic circuits, the pad frame typically contains a large number of free areas, which, however, typically cannot be used for digital circuits or larger analog circuit blocks.However, since an iQRNG according to the invention with an entropy source according to the invention and an electronic circuit according to the invention for generating and outputting a digital random number sequence is correspondingly small due to its extremely compact design, and the subsequent circuitry also typically comprises only a small number of gates, this type of QRNG can nevertheless be fully or at least partially integrated into a conventional pad frame. Due to the extremely compact design of the iQRNG according to the invention, it can also be implemented in existing designs for integrated electronic circuits in a space-saving manner and without major effort. This significantly reduces space consumption compared to conventional approaches for integrating QRNGs. The advantages of an iQRNG according to the invention can thus be fully exploited.

[0321] The advantages of an iQRNG according to the invention over known implementations in the prior art are primarily based on the further miniaturization of the entire random number generator structure and the resulting high degree of integration and miniaturization of the generated structures. Due to the complete isolation of the PLC and the associated SPAD from the environment, the security of random number generation can be significantly increased. The directed vertical radiation from the Zener avLED used as the PLC also contributes to increased security and to a significant increase in the efficiency of random number generation, resulting in an increase in the random bit and random number rate.

[0322] Realizing a cointegration of a suitable photon source and a single-photon detector on the same vertical layout cross-section of a common substrate, especially when using a commonly used cost-effective planar technology (i.e., processing only from one substrate side and without using other complex approaches, such as hybrid integration, e.g., via a chiplet approach), has not been possible in the state of the art so far.

[0323] A second deep pn junction, provided using a novel BCD technology and formed below the pn junction of the SPAD, can be used as an additional photodetector for monitoring attacks, particularly from the back of the iQRNG substrate of the relevant node in the network according to the invention. The efficiency of the optical coupling into the associated SPADs, as well as the isolation and security, can be further increased through the use of internal metal and silicide mirrors. Compared to the prior art, the Zener avLED used as a photon source requires only a relatively low operating voltage of < 8 V. Furthermore, since the absorption length of the emitted visible light in silicon is short (i.e., the associated absorption coefficient is high), very good optical isolation between adjacent elements can be achieved.This enables arrangement in an array with high cell density and a resulting correspondingly high generation or entropy rate.

[0324] Further aspects of the present invention are disclosed in the dependent claims or in the following description of the drawings.

[0325] Short description of the characters

[0326] The invention is explained below in exemplary embodiments with reference to the accompanying drawings. They show:

[0327] Figure 1 is a schematic representation of a first embodiment of an iQRNG according to the prior art in plan view;

[0328] Figure 2 is a schematic representation of a second embodiment of an iQRNG according to the prior art in a side view;

[0329] Figure 3 is a schematic representation of a BCD substrate provided by a method for providing deep pn junctions in a BCD process and a TCAD representation of the resulting dopant distribution;

[0330] Figure 4 is a schematic representation of an exemplary first embodiment of an iQRNG according to the invention;

[0331] Figure 5 is a schematic representation of an exemplary second embodiment of an iQRNG according to the invention;

[0332] Figure 6 is a schematic representation of an exemplary third embodiment of an iQRNG according to the invention;

[0333] Figure 7 graphical representation of the dependence of a) SPAD current and b) the ratio between SPAD current and Zener current as a function of the Zener blocking voltage at different SPAD blocking voltages (less than, equal to, greater than the breakdown voltage) within an iQRNG according to the invention;

[0334] Figure 8 is a schematic representation of an exemplary electronic circuit of a quantum random number generator for generating and outputting a digital random number sequence;

[0335] Figure 9 is a schematic representation of an exemplary layout of an integrated electronic circuit with an iQRNG according to the invention in the pad frame in plan view;

[0336] Figure 10 is a schematic representation of a node in a distributed network in which each node is equipped with a comprehensive control device; and

[0337] Figure 11 is a schematic representation of a distributed network consisting of several nodes corresponding to FIG. 10.

[0338] Detailed description of the characters

[0339] Detailed embodiments will now be described, which are illustrated by way of example in the accompanying drawings. The effects and features of these embodiments will be described with reference to the accompanying drawings. Throughout the drawings, like reference numerals designate like elements, and redundant descriptions are omitted. The present disclosure may be embodied in various forms and should not be construed as limited only to the embodiments shown herein. Rather, these embodiments are provided as examples so that this disclosure will be thorough and complete, and will fully convey the aspects and features of the present disclosure to those skilled in the art.

[0340] Therefore, methods, elements, and techniques that are not necessary for a person skilled in the art to fully understand the aspects and features of the present disclosure may not be described. In the drawings, the relative sizes of elements, layers, and regions may be exaggerated for clarity.

[0341] As used herein, the term "and / or" includes all combinations of one or more of the listed elements. Furthermore, the use of "may" in describing embodiments of the present disclosure refers to "one or more embodiments of the present disclosure." In the following description of embodiments, the singular terms may also include the plural, unless the context clearly indicates otherwise.

[0342] Although the terms "first" and "second" are used to describe various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, a first element may be referred to as a second element, and similarly, a second element may be referred to as a first element, without departing from the scope of the present disclosure. Terms such as "at least one of," when preceded by a list of elements, modify the entire list, not just the individual elements of the list.

[0343] Terms such as "substantially," "approximately," and similar terms are used as approximations rather than degrees, and are intended to account for inherent variations in measured or calculated values ​​that will be recognized by those skilled in the art. When the term "substantially" is used in connection with a characteristic that can be expressed by a numerical value, unless otherwise defined, the term "substantially" means a range of at least + / - 5% of the value centered on the value.

[0344] Figure 1 shows a schematic representation of a first embodiment of an iQRNG (or the entropy source of an iQRNG) according to the prior art, in plan view. The representation is based on a corresponding figure in EP 3 529 694 B1 and shows the surface O of an associated substrate 110, into which the QRNG is integrated. A circular photon source 120 with a pn junction configured to provide photons is supplied with current via a corresponding contact and is thereby excited to emit individual photons 128. To detect the emitted photons 128, an associated single-photon detector 130 in the form of a SPAD is arranged next to the photon source 120.However, as in conventional hybrid approaches for photonic QNRGs, the photon source 120 and the single-photon detector 130 continue to be structurally and functionally separate elements that are simply arranged next to each other for integration in a common substrate.

[0345] A current pulse generated by the single-photon detector 130 upon absorption of a photon 128 can then first be registered and evaluated in an associated electronic sampling means 152, in particular to generate a bit sequence based on the number of photons detected in the single-photon detector 130. Furthermore, an electronic post-processing means 154 is provided, which is to be configured to process the binary sequences of the electronic sampling means 152 in such a way that a so-called "whitening" operation is performed. This whitening operation is to comprise a plurality of compression operations intended to improve the statistical properties of the generated binary sequences. The post-processing step is intended to increase the entropy level of the QRNG.However, it must be ensured that the compression operations used do not lead to a fundamental predictability of the generated random numbers by introducing deterministic dependencies in the application.

[0346] To increase the efficiency of random number generation, i.e., the effective entropy rate, the photonic part of the QRNG on the surface O of the substrate 110 is protected by a light-blocking layer 150 ("light inhibitor filter"), which serves to shade it from external light. The light-blocking layer 150 can be provided, in particular, by a metallization layer that can be applied directly during the production process, for example, using CMOS technology, as the last metallization level. This is intended to shield the photon detector 130 from external light and make it sensitive only to those photons that pass through the substrate 110 due to crosstalk from the photon source 120.In addition, the metallization layer is also intended to improve the optical coupling of the photons 128 emitted by the photon source 120 by reflecting them inwards and thus preventing them from exiting the surface O of the substrate 110.

[0347] A disadvantage of such a side-by-side arrangement of the optical components is the distance between the components, which reduces the coupling strength due to the low illumination angle and the potential photon absorption in the various materials. Furthermore, despite the partially applied light-blocking layer 150, there is still the potential for optical access and thus an attack from the surface O of the substrate 110 or even from the back of the substrate. This can be used, for example, to specifically inject or extract additional photons, ultimately influencing and compromising the counting statistics and thus the entropy of the generated random numbers.Furthermore, the illustration also shows that the individual photons 128 are emitted isotropically distributed in all spatial directions, so that only a fraction of the photons 128 can be detected by the photon detector 130 and thus statistically evaluated. This significantly reduces the efficiency of random number generation and, on the other hand, results in a large number of photons 128 being emitted unused into the substrate 110, where they may also be extracted elsewhere by observers or attackers or cause interference.

[0348] Figure 2 shows a schematic representation of a second embodiment of an iQRNG (or the entropy source of an iQRNG) according to the prior art in a side view. The representation is based on a corresponding figure from Khanmohammadi et al. (A. Khanmohammadi, R. Enne, M. Hofbauer and H. Zimmermann, “A Monolithic Silicon Quantum Random Number Generator Based on Measurement of Photon Detection Time,” in IEEE Photonics Journal, vol. 7, no. 5, pp. 1-13, Oct. 2015, Art no. 7500113). In this example, too, the basic structure of a side-by-side arrangement of a photon source 120 (Si LED), which is configured to emit individual photons 128, and a single-photon detector 130 (SPAD) is clearly visible. In contrast to the embodiment shown in FIG.In the arrangement shown in Figure 1, however, the photon source 120 is provided as a circular central element, which is essentially completely surrounded by a correspondingly adapted, circular-ring-shaped single-photon detector 130. The common radial axis of symmetry R lies accordingly in the center of the iQRNG formed in this way (or in the center of the entropy source formed in this way). The photon source 120 is realized by an n-well formed in a deep n-well ("deep n-well"), which is introduced into the surface O of the substrate 110 ("p-substrate") centrally around the radial axis of symmetry R. ++ -area as cathode 122 and a p ++ -region is supplied with current as anode 124. Outside the deep n-well, the single photon detector 130 is also connected to the surface O via an introduced n ++-region as cathode 132 and a p arranged further away from the radial symmetry axis R ++ -region is contacted as anode 134. A p-well ("p well") is connected below the cathode 132. Below the anode 134, however, a p-well ("p well") is formed in a deep p-well ("deep p well"). The photon source 120 is provided as an element within the structure of the photon detector 130, so that, in contrast to FIG. 1, they form a structural and functional unit.

[0349] In this example of an iQRNG (or the entropy source of an iQRNG) according to the prior art, the photons 128 are emitted into the substrate 110 essentially from all sides, so that the disadvantages already described for the embodiment according to FIG. 1 with regard to security against observers or attackers and reduced efficiency also apply. However, due to the specific design as a circular ring-shaped arrangement and the structural connection of the single-photon detector 130 with the photon source 120, the integration density can be further increased compared to FIG. 1. In addition to a smaller area requirement for forming the iQRNG (or the entropy source of the iQRNG), this also includes increased security against attacks and increased efficiency in random number generation or the entropy rate as advantages.This is particularly due to the fact that reducing all distances reduces the loss of photons 128 due to material absorption and unfavorable emission directions. Furthermore, this reduces the area available for potential attacks. Apart from this, however, it is still possible, in principle, for attackers to extract or inject individual photons 128, particularly at the surface O as well as at other locations on the substrate 110, in order to influence the counting statistics. Such a juxtaposition of the two optical components of a QRNG therefore has several disadvantages that have so far prevented particularly secure, compact, and reliable random number generation for SoC applications.

[0350] Figure 3 shows a schematic representation of a BCD substrate 110 provided with a method for providing deep pn junctions 50 and 52 in a BCD process and a TCAD representation of the resulting dopant distribution. An embodiment of a method for producing deep pn junctions 50 and 52 in a BCD process comprises providing a carrier substrate 10; introducing a first dopant to form a first region 22 (e.g., NBL) of the first conductivity type (negative for NBL) into a surface S of the carrier substrate 10; introducing a second dopant to form a second region 32 (e.g.,PBL) of the second conductivity type (positive for PBL) into the surface S of the carrier substrate 10, wherein the first region 22 (NBL) and the second region 32 (PBL) at least partially overlap; growing an epitaxial layer 40 on the surface S of the carrier substrate 10, wherein the first region 22 (NBL) and the second region 32 (PBL) spread by diffusion of the first dopant and the second dopant in the epitaxial layer 40 and thereby form a pn junction 50 lying in the epitaxial layer.

[0351] In the illustration, the first region 22 is a deep NBL layer and the second region 32 is a deep PBL layer. However, the sequence can be interchanged, so that the first region 22 can also be a deep PBL layer and the second region 32 can be a deep NBL layer. By appropriately adjusting the diffusion lengths of the individual dopants, the layer sequence of the pn junctions 50 and 52 can also be reversed. For example, in FIG. 3, the NBL and PBL layers at the pn junction 50 and 52 could also be interchanged.

[0352] The described method differs from conventional methods for providing BCD substrates 110 according to the prior art, in particular in that the first region 22 (NBL) and the second region 32 (PBL) at least partially overlap. In particular, immediately after the introduction of the second dopant, in a plan view of the surface S of the carrier substrate 10, the first region 22 or the second region 32 can completely overlap the other region (32, 22). Therefore, in the embodiment shown, immediately after the introduction of the second dopant to form the second region 32 (PBL), the second region 32 (PBL) lies completely in the first region 22 (NBL) in a plan view of the surface S of the carrier substrate 10.In order to form a pn junction 50 located in the epitaxial layer, the first and second dopant preferably have different diffusion properties in the carrier substrate 10 and / or in the epitaxial layer 40. In particular, the second dopant in the second region 32 (PBL), as shown, can have a higher diffusion mobility (and thus diffusion length) in the carrier substrate 10 and in the epitaxial layer 40 than the first dopant in the first region 22 (NBL).

[0353] To enhance diffusion, the carrier substrate 10 can be heated after the introduction of the first dopant and / or the second dopant. Furthermore, after the growth of the epitaxial layer 40, the carrier substrate 10 can be heated to enhance dopant diffusion. In the method presented, the first dopant and / or the second dopant can be introduced either maskless or using a mask process. In the BCD wafer shown, a complete overlay of the first region 22 (NBL) with a single second region 32 (PBL) can be assumed. Conventionally, however, the first and second regions 22 and 32 are formed spatially separate from one another. In particular, their distance is generally chosen to be at least large enough that even after the individual dopants have diffused out, no overlapping regions are created.

[0354] The TCAD (Technology Computer-Aided Design, TCAD) representation shown below the schematic diagram shows the dopant distribution within the contacted BCD substrate 110 for simulating a corresponding integrated diode structure. Due to the double structure shown in this embodiment, with an upper pn junction 50 in the epitaxial layer 40 and a lower pn junction 52 in the carrier substrate 10, the side view shown shows an effective constriction of the n-type region NBL enclosed in the area of ​​the pn junctions 50 and 52 by the two p-type regions PBL surrounding this n-type region NBL. Both pn junctions 50 and 52 can be configured to provide mutually independent SPADs with a doping density and field strength distribution suitable for generating an avalanche effect.

[0355] Using appropriate BCD substrates 110 for further use in BCD technologies, particularly deep-lying SPADs ("deepSPADs") can thus be produced. In particular, sufficient installation space remains above the provided SPADs for the integration of further optoelectronic components. According to the invention, a Zener avLED formed above the deep-lying SPAD can therefore be used, in particular, to realize a particularly compact, vertically constructed iQRNG, in which individual photons 128 are emitted by the Zener avLED preferably in the direction of the upper pn junction 50 and are thus provided for detection by a SPAD formed directly below the Zener avLED at the upper pn junction 50 as a single-photon detector (see FIG. 4 with the associated figure description).

[0356] Figure 4 shows a schematic representation of an exemplary first embodiment of an iQRNG 200 (or the entropy source) according to the invention. The integrated QRNG 200 shown comprises a photon source 120 and a single-photon detector 130, wherein the photon source 120 and the single-photon detector 130 are arranged vertically one above the other in a common substrate made of a semiconductor material. Preferably, the photon source 120 is a single-photon source (SPS) configured to provide only single or a few photons 128 simultaneously. Preferably, the photon source 120 is a light-emitting avalanche Zener diode (Zener-avLED) operated at an operating point below or close to the breakdown voltage. Preferably, the single-photon detector 130 is a single-photon avalanche diode (SPAD).

[0357] The iQRNG 200 (or its entropy source) is preferably formed in a BCD substrate 110 using BCD technology. The BCD substrate 110 preferably comprises a carrier substrate 10 and an epitaxial layer 40 grown on the carrier substrate 10. A deep pn junction 50 located in the epitaxial layer was created between the carrier substrate 10 and the epitaxial layer 40 by diffusion of dopants introduced into a surface S of the carrier substrate 10 below the epitaxial layer 40 (see FIG. 3). Preferably, the single-photon detector 130 forms an avalanche region in a region around the deep pn junction 50 and comprises an absorption region PW / HPW with a high-voltage p-type well HPW and a p-type well PW."p-type well") for converting photons into electron-hole pairs, with the absorption region PW / HPW directly adjacent to the regions NBL and PBL forming the deep pn junction 50. The fully developed high-voltage p-well HPW enables optimal connection of the deep pn junction 50 from the anode.

[0358] It is preferred that the deep pn junction 50 is formed at least partially between a deep n-layer NBL as cathode 132 and a deep p-layer PBL directly adjoining the deep n-layer NBL, the absorption region PW / HPW directly adjoins the deep p-layer PBL and is formed substantially as a p-region (optionally comprising an intrinsic region), and an anode 134 formed as a p+ region directly adjoins the absorption region PW / HPW.

[0359] In the illustrated embodiment, the respective anodes 124 and 134 of the photon source 120 and the single-photon detector 130 are combined. These can then be electrically contacted, for example, via a common second metallization MET2 on the surface S of the BCD substrate 110. A common and continuous second metallization MET2 can also achieve shading to shield the entire installation space below. The common anodes 124, 134 of the photon source 120 and the single-photon detector 130 are connected, on the one hand, via the p-well PW to the high-voltage p-well HPW and the deep p-layer PBL for contacting the first p-n junction 50, and, on the other hand, to the p-doped region (p-type body) PBODY for contacting the pn junction 121 of the photon source 120.The associated cathodes 122 and 132 are each individually configured, for example, and can be electrically contacted via a first associated metallization MET1 and are preferably connected to the reference potential GND. The iQRNG according to the invention can be configured as a circular structure (corresponding to a spatial rotation of the illustrated plane around an imaginary central axis in the vertical direction). However, other configurations of the illustrated structure are also possible.

[0360] For the voltage supply, the cathode 132 of the single-photon detector 130 can be connected, for example, via a load resistor R2 to a preferably monitored second positive supply voltage on a second supply voltage line V ENT2. Upon detection of a photon, an electric current flows through the reverse-biased pn junction 50 of the single-photon detector 130. This results, for example, in a voltage drop across the load resistor R2 in the form of a typically rapidly rising and then exponentially falling voltage signal 405 at the output of the entropy source (for further possible processing, reference is made to the exemplary electronic circuit of a quantum random generator 400 shown in FIG. 8). For example, an analog-to-digital converter (ADC) (403 in FIG. 8) can subsequently evaluate this entropy output signal. The ADC (403) can also include amplifiers and / or filters for conditioning the voltage signal (405). The load resistor R2 also limits the current through the single-photon detector 130.

[0361] The cathode 122 of the single-photon detector 130 can, for example, be connected via a first load resistor Ri to a preferably monitored first positive supply voltage on a first supply voltage line VENTI. The first load resistor Ri limits the current through the photon source 120. Upon emission of a photon, the reverse current of the reverse-biased pn junction 121 of the photon source 120 typically exhibits a spike-like increase. This reverse current increase leads to a voltage pulse across the first load resistor Ri. This voltage pulse can be evaluated. For example, the ADC (403) can be configured, using an ADC-internal correlation device, to evaluate only those pulses on the voltage signal 405 at the output of the entropy source that correlate with a voltage pulse at the first load resistor Ri, for example, on an optional correlation signal 430.Only those pulses on the voltage signal 405 are then counted as pulses of the single-photon detector 130 that correlate with the emission of a photon by the photon source 120. This increases the quality of the entropy of the provided quantum random numbers.

[0362] Figure 5 shows a schematic representation of an exemplary second embodiment of an iQRNG (or the entropy source) according to the invention. The embodiment shown largely corresponds to the first embodiment shown in FIG. 4. The reference numerals and their respective assignment to individual features therefore apply accordingly. Compared to FIG. 4, however, the high-voltage p-well HPW has been structurally replaced by a tapered high-voltage p-well HPW and a weakly n-doped or intrinsic epitaxial region NEPI. The high-voltage p-well HPW of the absorption region PW / HPW merely forms a narrow channel between the upper p-well PW (also shown in FIG. 2) and the deep p-layer PBL of the deep pn junction 50. The area surrounding the channel is defined by the weakly n-doped or intrinsic epitaxial region NEPI.Through the channel, the deep pn junction 50 can be connected from the anode without an additional punch through the weakly n-doped or intrinsic epitaxial region NEPI.

[0363] Figure 6 shows a schematic representation of an exemplary third embodiment of an iQRNG (or entropy source) according to the invention. The embodiment shown largely corresponds to the first embodiment shown in FIG. 5. The reference numerals and their respective assignment to individual features therefore apply accordingly. In comparison to FIG. 4, the channel-shaped high-voltage p-well HPW in the absorption region PW / HPW has been omitted, and the weakly n-doped or intrinsic epitaxial region NEPI extends over the entire lower area. In this respect, in comparison to FIG. 4, the high-voltage p-well HPW has been structurally replaced by a weakly n-doped or intrinsic epitaxial region NEPI. The deep pn junction 50 is thus only formed after an additional punch through the weakly n-doped or intrinsic epitaxial region NEPI.intrinsic epitaxial region NEPI is connected from the anode, which results in a decoupling of possibly several cells arranged next to each other in parallel.

[0364] Figure 7 shows a graphical representation of the dependence of a) the SPAD current and b) the ratio between SPAD current and Zener current as a function of the Zener reverse voltage at various SPAD reverse voltages (less than, equal to, or greater than the breakdown voltage) within an iQRNG according to the invention. The dependence shown under a) clearly shows that the SPAD current increases exponentially with the Zener reverse voltage in the range from 5.6 V to 6.6 V. This applies to all operating modes of the SPAD, i.e. below its own breakdown voltage (< VBD, linear range), close to the breakdown voltage (~ VBD, avalanche range), as well as above the breakdown voltage (> VBD), and thus also in Geiger operation. The lower curve shown under b) (< VBD) shows that the measured current ratio between the SPAD current and the Zener current for various Zener blocking voltages in the range 5.8 to 6.6 V is approximately 1:4000.In the breakdown voltage range (~ VBD) of the SPAD, the ratio increases to values ​​around 1:10. This is due to the so-called multiplication factor of the SPAD, which leaves the linear range in the breakdown voltage range. The upper curve shows the corresponding ratio for the SPAD operated above the corresponding breakdown voltage (> VBD) (approximately 1:1). This means that when the SPAD is operated above the corresponding breakdown voltage (> VBD), the generated photocurrent and the Zener current of the Zener avLED are approximately equal, and a clear measurement signal can be measured by coupling photons to the SPAD.

[0365] Figure 8 shows a schematic representation of an exemplary electronic circuit of a quantum random number generator 400 for generating and outputting a digital random number sequence. The entropy source 401 shown can be, in particular, a photon source 120 and a single-photon detector 130 of an iQRNG 200 according to the invention, wherein the iQRNG 200 (or its entropy source) is connected to the supply voltage via a first supply voltage line VENTI and a second supply voltage line V ENT2, which is connected to a voltage converter 408, is supplied with different supply voltages, for example, compared to a reference potential on a reference potential line GND. It should be noted that a general quantum random generator 400 (and in particular the one shown here as an example) can, in some embodiments, directly correspond to an inventive iQRNG 200, as shown as a semiconductor structure, for example, in FIGS. 4 to 6, with the addition of further circuit components. In particular, a photon source 120 and a single-photon detector 130 of an inventive iQRNG 200 can together be regarded as an entropy source 401 of the shown quantum random generator 400, i.e., even in an inventive iQRNG 200, the combination of a photon source 120 and a single-photon detector 130 can be referred to as an entropy source.A voltage signal 405 generated by the entropy source 401 is applied to an analog-to-digital converter (ADC) 403, which is connected via a reference voltage line V. RE F is first digitized and then transferred as a digital output signal 407 to a pulse extension circuit 406. The supply voltage line V EN T and the reference voltage line VR E F are monitored via a voltage monitor 413, with both the voltage converter 408 and the voltage monitor 413 being supplied with voltage via a positive supply voltage line VDD relative to the reference potential on the reference potential line GND. The voltage converter 408 is connected to the voltage monitor 413 via a voltage converter line 421.

[0366] Pulse extension circuit 406 can, in particular, be a monostable multivibrator (MF). The monostable multivibrator can be used to extend a pulse on the line of the digital output signal 407 of the ADC 403 depending on a certain predetermined system clock, for example, to a time length of at least one clock period of the system clock.

[0367] A synchronized voltage signal 415, i.e., for example, a pulse with a specific minimum length, is then output by the pulse extension circuit 406 and passed to a time-to-pseudo-random-number converter (TPRC) 404.3. This converter can be composed of one or more stages. For example, the TPRC 404.3 can comprise an analog instrument, a time-to-analog converter (TAC), and / or an analog-to-pseudo-random-number converter (APRC), which together can also provide a TPRC 404.3. The pseudorandom number generator of the TPRC 404.3 can comprise a feedback shift register which, depending on the design, shifts its values ​​one place to the left or right with each clock pulse of the system clock and feeds the feedback value of a given feedback polynomial into the released bit.The feedback polynomial can preferably be a simple primitive feedback polynomial. The TPRC 404.3 can be directly connected to an internal data bus 419. The output signal 410 of the TPRC 404.3 can also be fed to an entropy extraction unit 404.4.

[0368] Starting with a starting value of the pseudorandom number generator (a so-called seed value), exactly one pseudorandom number of the pseudorandom number generator can be bijectively assigned to each clock pulse of the system clock starting from a falling edge of the synchronized voltage signal 415, ie the time position of the relevant clock pulse of the system clock after the falling edge of the synchronized voltage signal 415 can then be deduced from the value of the pseudorandom number.

[0369] Instead of a conventional digital counter as in the prior art, a pseudorandom number generator can thus be used. The advantage is that even if an attacker successfully introduces a disturbance into the synchronized voltage signal 415, the randomness of the quantum random bit at the output 411 of the entropy extraction 404.4 is only marginally disturbed, since the attacker would have to know the corresponding feedback polynomial. This can preferably be randomly selected from a multitude of possibilities. The same applies to the seed value of the pseudorandom number generator, which an attacker would then also have to determine. A further advantage of a pseudorandom number generator instead of a simple digital counter is the smaller space requirement of the feedback logic using a simple primitive feedback polynomial compared to a binary counter.If the linear feedback shift register of the pseudorandom number generator is long enough, each clock pulse between two pulses of the voltage signal 405 generated by the entropy source 401 is typically assigned a unique pseudorandom number.

[0370] Entropy extraction 404.4 can be used to determine an error (i.e., an undesired state) in the output signal 410 of TPRC 404.3. For this purpose, entropy extraction 404.4 can, in particular, comprise two linear feedback shift registers that can be compared with one another via a comparator. Conventional binary counters can therefore be dispensed with here as well. Depending on the register depth, feedback can also be provided via simple primitive polynomials as feedback polynomials. The length of the linear feedback shift registers can be freely adjustable. Long shift registers generally have a lower data rate and improved random statistics. Shorter shift registers, on the other hand, allow a higher data rate but exhibit a poorer random distribution.The use of shift registers here has the advantage of requiring fewer gates than in the prior art, reducing the logic depth of the circuits, and thus allowing for a higher clock rate. This reduces the probability of two identical numbers occurring and increases the random bit rate.

[0371] A corresponding method for entropy extraction can provide that two values ​​of the output signal 410 of the TPRC 404.3 are first determined and stored in shift registers of the entropy extraction 404.4. If two values ​​are stored in the shift register of the entropy extraction 404.4, the entropy extraction 404.4 can compare these two values. The values ​​in the shift registers of the entropy extraction 404.4 thus comprise a first value and a second value, both of which were determined by the TPRC 404.3. The entropy extraction 404.4 can then evaluate the two values. If the first value is smaller than the second value and the difference between the first value and the second value is greater than a minimum difference e, the entropy extraction 404.4 can set the value of its output 411 to a first logical value.If the first value is greater than the second value and the difference between the first value and the second value is greater than the minimum difference e, the entropy extraction 404.4 can set its output 411 to a second logical value that is different from the first logical value. If the difference between the first value and the second value is smaller than the minimum difference e, the entropy extraction 404.4 can discard the first value and the second value.

[0372] In such a case, entropy extraction 404.4 preferably causes a so-called watchdog 404.5 to increment an error counter by a first error counter increment. The first error counter increment may be negative. Conversely, entropy extraction 404.4 may decrement the error counter of watchdog 404.5 by a second error counter increment if the difference between the first value and the second value is greater than the minimum difference e. The second error counter increment may be equal to the first error counter increment.

[0373] Watchdog 404.5 is also connected to internal data bus 419. Additionally, watchdog 404.5 can be connected to voltage monitor 413 via one or more, preferably digital, input / output signal lines 414. Watchdog 404.5 preferably monitors the voltage values ​​determined by voltage monitor 413. It has proven useful for voltage monitor 413 to determine and monitor not only the voltages in quantum random generator 400, but also other voltages within the respective application circuit. Voltage monitor 413 can be, for example, an ADC.

[0374] The actual task of watchdog 404.5, however, is to monitor the quantum random number RN at output 411 of entropy extraction 404.4. Watchdog 404.5 can preferably detect at least three defined error cases. Watchdog 404.5 can forward valid quantum random bits at output 411, generating a seed value S 412, to an optional additional linear feedback shift register as a backup pseudorandom number generator (PRNG) 404.6. Preferably, watchdog 404.5 prevents the use of the valid quantum random bits by a finite state machine 404.8. If an error occurs, watchdog 404.5 can set certain error bits for further evaluation.

[0375] If, for example, the watchdog 404.5 has detected an error in the quantum random generator 400, it can preferably put the quantum random generator 400 into an emergency state. To do so, the watchdog 404.5 preferably sets a selection signal 416 of a signal multiplexer 404.7 downstream of the random number generation, so that the signal multiplexer 404.7, instead of the random numbers RN at the output 411 of the entropy extraction 404.4, applies the pseudorandom number PRN of the optional PRNG 404.6 in the form of a stream of pseudorandom bits via a pseudorandom signal line 417 to the input of the finite state machine 404.8 as a replacement for the at least potentially faulty random number RN of the output 411 of the entropy extraction 404.4.

[0376] The optional additional linear feedback shift register of the PRNG 404.6 can be configured to generate pseudorandom numbers PRN. The seed value S 412 preferably comprises the last valid quantum random bits of the output 411 of the entropy extraction 404.4. The watchdog 404.5 then preferably applies these last valid quantum random bits at the output 411 to the input of the optional PRNG 404.6. The seed value S can thus be used as a random, secure starting value for a generator polynomial of the feedback of the optional additional linear feedback shift register of the PRNG 404.6 for generating the pseudorandom number PRN and signaling it via the pseudorandom signal line 417. The generator polynomial and the degree of the generator polynomial are preferably freely selectable. The optional backup pseudo-random number generator can enable the provision of secure random numbers, at least temporarily, in the event of an error.

[0377] The finite-state machine 404.8 is responsible for receiving the random number RN or the pseudorandom number PRN at the output of the signal multiplexer 404.7 and writing corresponding quantum random data words 418 via a pseudorandom signal line 417 into a volatile memory (RAM) or a FIFO (First In - First Out) memory 404.9. If the write operation is successful, the finite-state machine 404.8 can set a finish flag 404.10 via the internal data bus 419. A processor can then access the volatile memory (RAM) or a FIFO (First In - First Out) memory 404.9, for example, and read the random number, for example, for encryption.

[0378] The quantum random generator 400 may further comprise a temperature sensor or other sensors with which the watchdog 404.5 or another device part of the quantum random generator 400, possibly by means of the ADO 403 or another analog-to-digital converter and / or other device parts such as sensor amplifiers and / or filters, monitors physical parameters of the environment of the quantum random generator 400, such as the temperature, and initiates countermeasures if a value of such a physical parameter lies outside a predetermined value range. Such countermeasures may include signaling to other devices, for example via the internal data bus 419 or an emergency operation, e.g., using the PRGNG 404.6 and the multiplexer 404.7, and / or changing internal operating parameters, such as the voltage levels of the internal supply voltages, e.g.,by means of the voltage converter 408 and / or the switching off of the random number generation, etc. This closes side channels for influencing the quantum random generator 400.

[0379] Figure 9 shows a schematic representation of an exemplary layout of an integrated electronic circuit 500 with an iQRNG 200 according to the invention (or its entropy source) in the pad frame 503, in a top view. The integrated electronic circuit 500, for example a microcontroller, has an inner region 505 in which the essential subcircuits of the integrated electronic circuit 500 are located. Typically, the inner region 505 is surrounded by a wiring region 504, in which, above all, supply voltage lines, data bus lines, and other lines can be routed.

[0380] The wiring area 504 and the inner area 505 of the integrated electronic circuit 500 are typically surrounded by the pad frame 503 (also referred to as pad edge), which includes the connection pads 502 (connection areas) for the electrical bonds or other electrical connections.

[0381] Preferably, an iQRNG 200 according to the invention or a corresponding quantum random generator 400 (or their entropy sources), as shown, for example, in Figure 8, can be placed entirely or at least in substantial parts in the pad frame 503, since the gaps between the individual connection pads 502 are often not filled with electronic circuit components. However, these gaps must still be processed during the manufacture of the integrated electronic circuit 500 and therefore cause unnecessary manufacturing costs. Placing an iQRNG 200 according to the invention or corresponding quantum random generators 400 (or their entropy sources) entirely or at least in substantial parts in the pad frame 503 therefore significantly reduces the additional costs for their provision. In particular, at least the photon source 120 and the single-photon detector 130 (entropy source 401) can preferably be placed in the pad frame 503 between two connection pads 502.Furthermore, an ADC 403, a voltage converter 408 for supplying energy to the entropy source 403, a pulse extension circuit 406 and / or analog parts of a quantum random generator 400 according to the invention (e.g., an amplifier) ​​can also be placed in the pad frame 503 between two connection pads 502.

[0382] Figure 10 shows a schematic representation of a node in a distributed network in which each node is equipped with a comprehensive control device. The control device can be designed to integrate a variety of components essential for the operation, communication, and security of the node. The control device of each node plays a central role in secure and efficient communication within the network.

[0383] The control device 1000 may include a quantum random number generator 1010, a CPU 1020, a volatile memory 1040, a non-volatile memory 1050, an encryption and decryption unit 1060, an internal data bus 1030, a voltage regulator 1070, a reset circuit 1080, an interrupt controller 1090, a clock system 1100 with oscillator 1110, a JTAG test interface 1120, and an optional watchdog 1130. The control device 1000 is configured to perform security-relevant tasks and control communication between the nodes in the network, with the random numbers of the quantum random number generator 1010 being used for cryptographic applications.

[0384] At the heart of the control device is a central processing unit (CPU), which can handle all computations and control tasks within the node. The CPU can be configured to execute a variety of computer- and / or machine-implemented methods to encrypt data messages, generate and verify signatures, generate keys and key pairs, and use spreading codes and watermarks to mark and conceal information. This wide range of functions can be supported by the tight integration of the CPU with other components of the control device.

[0385] The internal data bus can connect the CPU to all other components of the control device, thus enabling efficient communication between them. The CPU can use the internal data bus to control the control device's quantum random number generator, read the generated random numbers, and, if necessary, receive interrupt signals that can indicate a specific activity or error condition. The quantum random number generator is particularly important here, as it contributes to the generation of random numbers with high quality and bit rate.According to the invention, such a respective quantum random number generator preferably comprises an entropy source fabricated monolithically in a semiconductor substrate, which comprises a single-photon source and a single-photon detector, which in turn are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate, the aforementioned bit data rate. The respective quantum random number generator can comprise means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source.

[0386] In addition to the quantum random number generator, the CPU can also communicate with the controller's volatile and non-volatile memory via the internal data bus. Temporary data and programs can be stored in volatile memory, while non-volatile memory can be used for long-term storage of keys and other security-relevant information. The CPU can access the memory to read and write required data.

[0387] Another critical element of the control device is the encryption and decryption unit, which can also be connected to the CPU via the internal data bus. This unit is responsible for encrypting and decrypting incoming and outgoing data messages. Encryption is preferably performed using the random numbers generated by the quantum random number generator, which according to the invention preferably comprises an entropy source fabricated monolithically in a semiconductor substrate. This entropy source preferably comprises a single-photon source and a single-photon detector, which are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate, the aforementioned bit data rate, and quantum computer-secure encryption.The respective quantum random number generator may comprise means for operating the entropy source and means for generating quantum random numbers in dependence on the entropy source output signal of the entropy source.

[0388] The CPU can also control the voltage regulator via the internal data bus, which can provide the necessary internal supply voltages for the control device. The voltage regulator can ensure that all components of the control device receive a stable power supply, which is crucial for the reliable operation of the entire device.

[0389] A reset circuit can also be present and controlled by the CPU to restart the control device in a defined state if necessary. The CPU can activate this reset circuit and monitor its state via the internal data bus.

[0390] The interrupt controller is another important element that can communicate with the CPU. This controller can collect and manage all interrupt signals issued by the various components of the control device and forward them to the CPU. The CPU can receive these signals via the internal data bus and take appropriate action.

[0391] The clock system, which can be driven by an oscillator, can ensure precise control of the timing processes within the control device. The CPU can synchronize its activities with the clock system, which can also be connected to the CPU via the internal data bus. The oscillator can provide the base frequency, which is crucial for the clock speed of the CPU and the other components.

[0392] Another important interface of the controller is the JTAG test interface, which can enable testing and debugging of the controller. This interface, which can optionally also support boundary scan, can be connected to the CPU via the internal data bus and allows the controller's state to be read and analyzed.

[0393] An optional watchdog monitors both the correct operation of the CPU and the status of the quantum random number generator. The watchdog can be equipped with an ADC (analog-to-digital converter) that can measure the voltages within the control device, in particular the operating voltages of the quantum random number generator. Additionally, the watchdog can monitor the entropy quality of the random numbers generated by the quantum random number generator. This monitoring can ensure that the quantum random number generator continuously generates high-quality random numbers and that any deviations or malfunctions can be detected early. The watchdog can communicate with the CPU via the internal data bus, providing it with monitoring data and any warning signals. The control device can also include multiple data interfaces through which the CPU can communicate with other nodes in the network.These data interfaces enable the exchange of data messages between nodes, with communication preferably encrypted using random numbers generated by the quantum random number generator. These encrypted data messages ensure the security of communication and protect the transmitted information from unauthorized access.

[0394] In addition to the components described above, the control device can integrate additional components that are often found in modern IoT networks, especially automotive networks. These include sensors for acquiring environmental data, communication modules for wireless networks, or even special security modules for processing cryptographic algorithms. These additional components can also be connected to the CPU via the internal data bus and thus be seamlessly integrated into the control device.

[0395] The control device shown in FIG. 10 demonstrates a highly integrated and powerful architecture optimized for operation in distributed networks. The vertical arrangement of the respective photon source and the respective photodetector perpendicular to the surface of the respective semiconductor substrate, in which the respective entropy source of the respective quantum random number generator is preferably manufactured monolithically, plays a central role, as it contributes to the respective generation of respective random numbers with high quality and bit data rate in the respective node of the network. The CPU can control and monitor all components of the control device and ensure that they work together smoothly and efficiently to guarantee the security and reliability of the node in the network.

[0396] In particular, FIG. 10 shows a schematic representation of an exemplary embodiment of a node in a distributed network, which includes a central control device 1000. This control device 1000 is designed to perform safety-critical tasks in the network and to control communication between the nodes. Each node can operate autonomously and is equipped with a hardware-based quantum random number generator 1010, which generates the random numbers with high quality and bit data rate. This is ensured by the entropy source of the quantum random number generator, preferably manufactured monolithically in a semiconductor substrate.This entropy source preferably comprises a single-photon source and a single-photon detector, which are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate, the aforementioned bit data rate, and a particularly high random quality, as well as quantum computer-secure encryption. The respective quantum random number generator comprises means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source.

[0397] The control device 1000 includes a central processing unit (CPU) 1020, which performs all calculations and control tasks. The CPU 1020 is configured to execute computer- and / or machine-implemented methods to encrypt data messages, generate signatures, verify signatures, generate keys and key pairs, and use spreading codes and / or watermarks to mark and conceal information. These tasks are supported by the tight integration of the CPU 1020 with other components of the control device.

[0398] An internal data bus 1030 connects the CPU 1020 to all other device components of the control device 1000 and enables efficient communication between them. Via the internal data bus 1030, the CPU 1020 controls the quantum random number generator 1010, reads the generated random numbers, and receives interrupt signals from the quantum random number generator 1010 when certain events occur. The quantum random number generator 1010 utilizes the entropy source of the quantum random number generator 1010, which is preferably manufactured monolithically in a semiconductor substrate according to the invention, to integrate this high-quality entropy source into this proposed network node and thus into the proposed subnetwork and thus into the proposed network.This entropy source preferably comprises a single-photon source and a single-photon detector, which are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate, the aforementioned bit data rate, and a particularly high random quality, as well as quantum computer-secure encryption. The respective quantum random number generator 1010 comprises means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source.

[0399] The CPU 1020 also communicates with the volatile memory 1040 and the non-volatile memory 1050 via the internal data bus 1030. The volatile memory 1040 is used for temporary storage of data and programs during runtime, while the non-volatile memory 1050 stores security-relevant information, such as cryptographic keys, for the long term. The CPU 1020 can access the non-volatile memory 1050 at any time to read or write cryptographic keys required for secure communication on the network.

[0400] For encrypting and decrypting data messages with other nodes in the network, the control device 1000 is equipped with an encryption and decryption unit 1060. This unit 1060 is controlled by the CPU 1020 via the internal data bus 1030, and the CPU 1020 reads the processed data and receives interrupt signals from the unit 1060 when special cryptographic processes are running. Communication between the nodes in the network is preferably encrypted using the random numbers generated by the quantum random number generator 1010. To generate these random numbers with high quality and a high random number rate, the quantum random number generator 1010 preferably comprises an entropy source of the quantum random number generator 1010, which is fabricated monolithically in a semiconductor substrate.This entropy source preferably comprises a single-photon source and a single-photon detector, which are arranged perpendicular to each other and to the surface of the respective semiconductor substrate, enabling a particularly high random number data rate, the aforementioned bit data rate, and a particularly high random quality, as well as quantum computer-secure encryption of communication in the subnetwork or network. The respective quantum random number generator 1010 comprises means for operating the entropy source and means for generating quantum random numbers depending on the entropy source output signal of the entropy source.

[0401] A voltage regulator 1070 within the control device 1000 provides the internal supply voltages. The CPU 1020 controls the voltage regulator 1070 via the internal data bus 1030 and monitors the voltage levels to ensure a stable power supply to the control device 1000.

[0402] The reset circuit 1080 enables the CPU 1020 to reset the control device 1000 to a defined initial state when needed. This is particularly relevant in error or fault situations to ensure the functionality of the control device 1000. The CPU 1020 controls this reset circuit 1080 via the internal data bus 1030. An interrupt controller 1090 collects and manages all interrupt signals generated by the various device components of the control device 1000. The CPU 1020 receives these signals via the internal data bus 1030 and processes them to respond quickly to critical events.

[0403] The clock system 1100, driven by an oscillator 1110, ensures the precise synchronization of the processes within the control device 1000. The CPU 1020 is connected to the clock system 1100 via the internal data bus 1030 and synchronizes its activities according to the clock signals generated by the oscillator 1110.

[0404] A JTAG test interface 1120, which optionally also features boundary-scan functionality, is integrated into the controller 1000 to support external diagnostic and debugging functions. The CPU 1020 is connected to the JTAG test interface 1120 via the internal data bus 1030 and can read diagnostic data and initiate tests.

[0405] An optional watchdog 1130 continuously monitors the functionality of the CPU 1020 and the quantum random number generator 1010. The watchdog 1130 is equipped with an ADC 1140, which monitors the power supply and the entropy quality of the random numbers. If a deviation from normal operating conditions is detected, the watchdog 1130 can reset the CPU 1020 or the quantum random number generator 1010 to ensure the functionality of the control device 1000.

[0406] Preferably, the CPU 1020 of the control device 1000 is capable of executing a computer- and / or machine-implemented method for generating cryptographic keys and initialization vectors (IVs). These keys and IVs can be stored in the volatile memory 1040 and used in security-critical applications, which can be supported by the encryption and decryption unit 1060.

[0407] Preferably, the CPU 1020 can execute a computer- and / or machine-implemented method for generating one-time passwords (OTPs), which can serve as an additional security layer for authentication on the network. These OTPs are based on the random numbers generated by the quantum random number generator 1010 and can be managed in the volatile memory 1040.

[0408] To support secure communication protocols, CPU 1020 can preferably execute a computer- and / or machine-implemented method for executing TLS or IPsec protocols. The random numbers of quantum random number generator 1010 can be used to securely negotiate session keys, which can then be used by encryption and decryption unit 1060 to encrypt the data messages.

[0409] Preferably, CPU 1020 can execute a computer- and / or machine-implemented method for randomly selecting nodes in the network, ensuring that the selection processes are fair and tamper-proof. The random numbers generated by quantum random number generator 1010 can serve as the basis for randomly distributing tasks in the network.

[0410] Additionally, the control device 1000 can support the use of physical phenomena such as thermal noise or quantum processes in a computer- and / or machine-implemented method for generating high-quality random numbers. These random numbers can then be used for safety-critical applications in the network.

[0411] For amplification and filtering of the entropy source, the CPU 1020 can execute a computer- and / or machine-implemented process that ensures that the entropy source signal is optimally amplified and filtered before being converted into random numbers. This ensures high quality and reliability of the generated random numbers.

[0412] Preferably, the CPU (1020) can execute a computer- and / or machine-implemented method for post-processing the generated random numbers. Various techniques such as hashing or XORing can be used to further improve the quality of the random numbers and eliminate systematic errors.

[0413] To securely store and control access to security-relevant data, the CPU 1020 may execute a computer and / or machine-implemented method that regulates access to the non-volatile memory 1050 and ensures that only authorized processes can access this data.

[0414] Preferably, the CPU 1020 can execute a computer- and / or machine-implemented method for continuous monitoring and error detection to ensure that the control device 1000 remains functional at all times. This preferably also includes automatic recovery in the event of a failure to preserve the integrity of the system. Furthermore, the control device 1000 can perform additional functions that can be controlled by the CPU 1020. This includes, for example, the implementation of error detection and recovery processes, the management and use of digital certificates, the support of consensus mechanisms in distributed networks, and / or the execution of additional security and optimization protocols to maximize the performance and security of the network.

[0415] To implement the corresponding functions in the node's control device 1000, the CPU 1020 may execute various computer and / or machine-implemented methods specifically tailored to the requirements of these functions.

[0416] For load balancing in the network, CPU 1020 can execute a computer- and / or machine-implemented method for dynamically managing network resources. For example, CPU 1020 can analyze the current utilization of the nodes in the network and distribute tasks so that individual nodes are not overloaded. The internal data bus 1030 can enable CPU 1020 to access and efficiently process the necessary information to distribute the load evenly across the network.

[0417] To continuously monitor the network and detect anomalies, the CPU 1020 can execute a computer- and / or machine-implemented process that monitors network activity and identifies irregularities in real time. The interrupt controller 1090 can play an important role in this by preferentially providing the CPU 1020 with all relevant signals that could indicate unusual activity or potential security threats. This information is evaluated by the CPU 1020 via the internal data bus 1030 to quickly respond to any problems that arise.

[0418] To manage digital certificates and their use in the network, the CPU 1020 can execute a computer- and / or machine-implemented method that includes generating, storing, and distributing certificates. The CPU 1020 preferably accesses the non-volatile memory 1050 to securely store the certificates and retrieve them when needed. These certificates can be used to ensure the authenticity and integrity of communication in the network, with the CPU 1020 using the encryption and decryption unit 1060 to securely transmit the certificate-based data. To implement consensus mechanisms in distributed networks, the CPU 1020 can execute a computer- and / or machine-implemented method that ensures that all nodes in the network have a unified view of the current state of the network.To this end, the CPU 1020 preferentially uses the random numbers generated by the nodes to ensure fair and tamper-proof consensus processes. These processes can be supported by the quantum random number generator 1010, which can be connected to the CPU 1020 via the internal data bus 1030 and can provide the random numbers required for consensus.

[0419] To ensure network scalability and resilience, CPU 1020 can execute a computer- and / or machine-implemented process for managing and integrating new nodes into the network. CPU 1020 can ensure that new nodes are seamlessly integrated into the existing network and can immediately contribute to overall performance and security. Internal data bus 1030 can enable CPU 1020 to make the necessary settings and coordinate communication between the new and existing nodes.

[0420] In summary, FIG. 10 illustrates a comprehensive and highly integrated control device 1000 that provides all the necessary functions for secure, efficient, and scalable communication in a distributed subnetwork or network. The CPU 1020 preferably controls and monitors all processes in the network node of which the control device is a part, of which the respective CPU 1020 is a part.

[0421] The use of quantum random number generators 1010 according to the invention in the control devices of the network nodes of the subnetwork according to the invention enables them to play a central role in ensuring network performance and security. The respective entropy sources of the respective quantum random number generators, which are preferably manufactured monolithically in a respective semiconductor substrate according to the invention, ensure the respective random quality and the respective high overall random number rate with respect to the respective entire subnetwork according to the invention.These respective entropy sources preferably each comprise, according to the invention, a respective single-photon source and a respective single-photon detector, which in turn can be arranged perpendicular to one another and to the respective surface of the respective semiconductor substrate in question, which enables a particularly high total random number data rate, the said total bit data rate, and a particularly high total random quality and the quantum computer secure encryption of the respective subnetwork of the network according to the invention.The respective quantum random number generators of the network nodes according to the invention preferably each comprise respective means for the respective operation of the respective entropy source and respective means for the respective generation of respective quantum random numbers in respective dependence on the respective entropy source output signal of the respective entropy source of the respective quantum random number generator of the respective control device of the respective network node of the respective subnetwork according to the invention of the network according to the invention.

[0422] Due to the close integration and interaction of the various device parts, the control device 1000 can reliably implement the tasks according to the invention and thus ensure a high degree of security and efficiency in the network.

[0423] Figure 11 shows a schematic representation of a distributed network of multiple nodes corresponding to FIG. 10. In particular, FIG. 11 illustrates a network of multiple nodes, each node equipped with a control device as described in FIG. 10. The nodes communicate with each other and can use the random numbers generated by the quantum random number generators 1010 to support secure communication protocols, generate cryptographic keys and initialization vectors (IVs), generate one-time passwords (OTPs), and randomly select nodes for specific tasks in the network. The decentralized structure of the network ensures high security, scalability, and resilience.

[0424] In this network, the individual nodes cooperate to ensure secure and efficient communication. The central element of the network is the decentralized structure, which is realized by the integration of hardware-based quantum random number generators in each node. According to the invention, these quantum random number generators preferably each comprise a respective entropy source of the respective quantum random number generator, manufactured monolithically in a semiconductor substrate. This respective entropy source preferably in turn comprises a respective single-photon source and a respective single-photon detector, which in turn are arranged perpendicular to one another and to the respective surface of the respective semiconductor substrate.This enables a particularly high respective random number data rate, the said respective bit data rate, and a particularly high respective random quality, as well as the respective quantum computer-secure encryption of the respective communication of the respective network node of the inventive network. This enables a particularly high overall random number data rate, the said overall bit data rate, and a particularly high overall random quality, as well as the quantum computer-secure encryption of the communication in the inventive network, for the entire inventive subnetwork of the inventive network. The respective quantum random number generators in the network preferably each comprise respective means for operating the entropy source and respective means for generating respective quantum random numbers depending on the respective entropy source output signal of the respective entropy sources.The use of the quantum random number generators according to the invention in the network nodes of the network according to the invention leads overall to an improved overall random quality of the random numbers in the network and a higher overall random bit data rate in the network according to the invention.

[0425] In the schematic representation of FIG. 11, several nodes are connected by lines that represent the communication paths between the individual nodes. Each node is capable of autonomously generating random numbers and using them to encrypt and authenticate the communication data.

[0426] This is done by the respective quantum random number generators of the network according to the invention, preferably in each respective node of the network according to the invention.

[0427] Preferably, the respective quantum random number generators each comprise a respective entropy source of the respective quantum random number generator 1010, which is manufactured monolithically in a semiconductor substrate. This respective entropy source preferably in turn comprises a respective single-photon source and a respective single-photon detector, which in turn are each arranged perpendicular to one another and to the respective surface of the respective semiconductor substrate in question, which enables a particularly high respective random number data rate, the said respective bit data rate, and a particularly high respective random quality and the respective quantum computer secure encryption of the communication in the subnetwork according to the invention or in the network according to the invention.The respective quantum random number generator 1010 preferably comprises respective means for the respective operation of the respective entropy source and respective means for the respective generation of respective quantum random numbers in each case as a function of the respective entropy source output signal of the respective entropy source. This makes it possible to ensure a particularly high respective random quality and respective density of the respective random numbers. This, in turn, ensures a particularly high overall random quality and overall density of the random numbers in the subnetwork of the network according to the invention.

[0428] Advantages of decentralization: The decentralized arrangement of nodes in the network significantly increases security. Since each node generates its own random numbers, there is no central point that could compromise the entire network. Should a single node be compromised, the integrity of the random numbers in the remaining nodes remains unaffected, strengthening the security of the network as a whole.

[0429] Another advantage of decentralization is increased reliability. If one node fails, the remaining nodes can continue to perform their functions without affecting the overall functionality of the network. This is particularly important in safety-critical applications where continuous availability and integrity of communication are required.

[0430] Efficiency and scalability: The network structure shown in FIG. 11 also enables high efficiency and scalability. By evenly distributing random number generation across all nodes, the load is evenly distributed, avoiding bottlenecks and performance degradation. Each node contributes to the overall entropy of the network, resulting in even and efficient resource utilization.

[0431] The network can be easily scaled by adding new nodes, each equipped with its own quantum random number generator. This allows for flexible adaptation to growing demands without significant changes to the existing infrastructure. The new nodes integrate seamlessly into the network and contribute to overall performance and security.

[0432] Collaborative security protocols: Decentralized random number generation also allows nodes in the network to implement collaborative security protocols. These protocols use the random numbers generated by each node for secure communication, key exchange, and authentication.Since the respective random numbers are based on physical phenomena within the respective entropy sources and since the respective entropy sources preferably comprise respective single-photon sources and respective single-photon detectors directly coupled to these, which in turn are arranged perpendicular to one another and to the respective surface of the respective semiconductor substrate in question, which enables a particularly high random number data rate, the said respective bit data rate, and a particularly high respective random quality and the respective quantum computer secure encryption of the respective communication in the sub-network or network, they offer a particularly high level of security against manipulation and prediction.

[0433] This is typically achieved by a respective entropy source of the respective quantum random number generator 1010, which is manufactured monolithically in a semiconductor substrate. This respective entropy source preferably in turn comprises a respective single-photon source and a respective single-photon detector, which in turn are arranged perpendicular to one another and to the respective surface of the respective semiconductor substrate in question, which enables a particularly high respective random number data rate, the said respective bit data rate, and a particularly high respective random quality and the respective quantum computer-secure respective encryption of the respective communication in the subnetwork or network.The respective quantum random number generator 1010 preferably comprises respective means for the respective operation of the respective entropy source and respective means for the respective generation of respective quantum random numbers in respective dependence on the respective entropy source output signal of the respective entropy source.

[0434] For example, the network in FIG. 11 may use a distributed TLS protocol, where randomly generated keys are exchanged between nodes to establish secure communication channels. The random selection of nodes for specific tasks, such as validating transactions in a blockchain network, is also supported by the decentralized structure, making tampering and targeted attacks more difficult.

[0435] Reduced latency: The network structure shown in FIG. 11 also contributes to reducing latency. Because each node generates its own random numbers and is not dependent on a central node, the nodes can respond to requests and exchange data more quickly. This leads to overall faster and more efficient communication within the network.

[0436] Improved security through vertically integrated entropy sources: The vertical integration of the quantum random number generators' respective photon sources and photodetectors significantly improves the network's security features. They ensure that the generated random numbers are of the highest quality, which is crucial for secure encryption and authentication within the network. The resulting high bit rates of the random numbers enable the network to maintain secure and stable communication even under high data volumes.

[0437] Synchronization and Consensus: Another important feature of the network depicted in Figure 11 is the ability to synchronize and achieve consensus among nodes. Since random numbers are generated independently at each node, it is important that nodes synchronize their activities to ensure consistent and coherent results. This can be achieved by implementing consensus protocols that ensure that all nodes in the network act based on the same random events.

[0438] The synchronization of the nodes is supported by the high quality and speed of random number generation, which is made possible by the vertical integration of the respective photon sources and the respective photodetectors of the respective entropy sources of the quantum random number generators. This ensures that all nodes can operate synchronously without inconsistencies or delays.

[0439] Health check and self-monitoring: Another central element of the network in FIG. 11 is the self-monitoring of the nodes, particularly through the watchdog, which can be integrated into each node. This watchdog not only monitors the correct functioning of the central processing unit (CPU) but can also perform regular health checks on the quantum random number generator. The watchdog can continuously check the operating voltages and the entropy quality of the random numbers to ensure that the quantum random number generator is functioning properly.

[0440] This monitoring function helps increase network security and reliability. If the watchdog detects anomalies, it can isolate the affected nodes or issue alerts to minimize potential security risks.

[0441] Communication between nodes: The nodes in the network can communicate with each other via the data interfaces of their control devices. This communication is preferably encrypted, whereby the random numbers of the quantum random number generator can be used for encryption. The high quality of the random numbers, ensured by the vertical integration of the respective photon sources and the respective photodetectors of the respective entropy sources of the quantum random number generators, ensures that the communication channels between the nodes are secure and that the data is protected from unauthorized access.

[0442] Furthermore, the nodes can exchange various types of data, including encrypted data messages, digital signatures, and authentication data. This data can be securely stored in the memory modules of the control devices and processed by the CPU as needed. The CPU can control the entire communication process and can ensure that the data is correctly encrypted and decrypted before being forwarded or processed.

[0443] Extensibility and adaptability: The network depicted in Figure 11 is also extensible and adaptable. New nodes can be easily integrated into the network by simply connecting them to the existing communication channels. Each new node brings its own source of random numbers, further increasing the overall entropy and security of the network.

[0444] By leveraging the advantages of the vertical integration of the respective photon sources and the respective photodetectors of the respective entropy sources in the quantum random number generators, the network remains flexible and adaptable to changing requirements and new technologies. This makes the network future-proof and ready for use in a wide range of applications, from industrial control systems to IoT networks in the automotive industry.

[0445] Summary: Overall, FIG. 11 shows a robust and secure network based on decentralized random number generation. The vertical integration of the respective photon sources and the respective photodetectors of the respective entropy sources of the quantum random number generators contributes to the highest quality and high bit rate generation of the generated random numbers. These features not only improve the security and efficiency of the network but also enable fast and reliable communication between nodes. The network is scalable, flexible, and resilient to failures and attacks, making it an ideal solution for modern, distributed applications.

[0446] 10 Carrier substrate

[0447] 22 first area (e.g. NBL)

[0448] 32 second area (e.g. PBL)

[0449] 40 epitaxial layer

[0450] 50 first pn junction (e.g. upper pn junction of a double structure)

[0451] 52 second pn junction (e.g. lower pn junction of a double structure)

[0452] 110 Substrat

[0453] 120 photon source (e.g. single photon source, SPS)

[0454] 122 Cathode (n + , photon source)

[0455] 124 Anode (p + , photon source)

[0456] 128 photons

[0457] 130 Single-photon detector (e.g. single-photon avalanche diode, SPAD)

[0458] 132 Cathode (n + , single-photon detector)

[0459] 134 Anode (p + , single-photon detector)

[0460] 150 light blocking layer

[0461] 152 means of electronic recording

[0462] 154 Means of electronic post-processing

[0463] 200 iQRNG

[0464] 400 quantum random generators (e.g. based on an iQRNG)

[0465] 401 Entropy Source (e.g. iQRNG)

[0466] 403 Analog-to-Digital Converter (ADC)

[0467] 404.3 Time-to-Pseudo-Random Number Converter (English: Time-to-Pseudo-Random-

[0468] Number Converter (TPRC)

[0469] 404.4 Entropy extraction

[0470] 404.5 Watchdog

[0471] 404.6 Pseudo-random number generator (PRNG, e.g. linear feedback shift register)

[0472] 404.7 Signal Multiplexer

[0473] 404.8 Finite State Machine (FSM)

[0474] 404.9 volatile memory (RAM) / FIFO memory (First In - First Out)

[0475] 404.10 Finish Flag

[0476] 405 Voltage signal (entropy source) 406 Pulse extension circuit (e.g. monoflop, MF)

[0477] 407 Output signal (ADC)

[0478] 408 voltage converter

[0479] 410 Output signal (TPRC)

[0480] 411 Output (Entropy Extraction)

[0481] 412 Seed Value S

[0482] 413 Voltage Monitor

[0483] 414 digital input / output signal lines

[0484] 415 synchronized voltage signal (e.g. pulse with a minimum length)

[0485] 416 Selection signal

[0486] 417 Pseudorandom signal line

[0487] 418 quantum random data words

[0488] 419 internal data bus

[0489] 420 interrupt signal

[0490] 421 voltage transformer cable

[0491] 430 Correlation signal (optional)

[0492] 500 electronic circuits (Integrated Circuits, ICs)

[0493] 501 semiconductor die

[0494] 502 connection pads (connection surfaces)

[0495] 503 pad frame

[0496] 504 wiring area

[0497] 505 inner area

[0498] 1000 Node control device

[0499] 1010 quantum random number generator (e.g. 400, based on an iQRNG)

[0500] 1020 CPU (central processing unit);

[0501] 1030 internal data bus

[0502] 1040 volatile memory

[0503] 1050 non-volatile memory

[0504] 1060 Encryption and Decryption Unit

[0505] 1070 voltage regulator

[0506] 1080 reset circuit

[0507] 1090 interrupt controller 1100 clock system

[0508] 1110 Oscillator

[0509] 1120 JTAG test interface

[0510] 1130 Watchdog (e.g. 404.5)

[0511] 1140 ADC (analog-to-digital converter);

[0512] 1150 sensors for environmental data acquisition

[0513] 1160 communication modules for wireless networks

[0514] 1170 security modules for processing cryptographic algorithms

[0515] 1180 data interfaces for communication with other nodes in the network

[0516] NBL deep n-layer (n-type buried layer)

[0517] PBL deep p-layer (p-type buried layer)

[0518] H(V)PW high-voltage p-type well

[0519] H(V)NW high-voltage n-type well

[0520] PW p-well

[0521] PBODY p-doped region (p-type body)

[0522] NEPI weakly n-doped or (approximately) intrinsic epitaxial region

[0523] MET1. MET2 Metallization

[0524] CONT Contact

[0525] STI isolation region (shallow trench isolation) poly polysilicon layer

[0526] P + p + -Area

[0527] N + n + -Area

[0528] VDD positive supply voltage line

[0529] GND reference potential line

[0530] VENTI first supply voltage line (entropy source)

[0531] V E NT2 second supply voltage line (entropy source)

[0532] VREF Reference voltage line (ADC)

[0533] RN Random number (e.g. 1-bit random number)

[0534] PRN pseudorandom number

[0535] S Surface (carrier substrate, e.g. a BCD substrate)

[0536] O Surface (substrate, e.g. a BCD substrate)

Claims

Patent claims 1. A distributed network comprising a plurality of nodes, wherein each node of the plurality of nodes has at least one hardware-based quantum random number generator with at least one entropy source, wherein the quantum random number generator at each node is configured to generate truly random numbers, the network and / or sub-devices of the network are configured to use the random numbers to ensure the security, availability, and robustness of the network, and the network and / or sub-networks of the network and / or sub-devices of the network are configured to perform the random number generation in a decentralized manner, such that no central node is required to generate or manage random numbers, wherein the quantum random number generator comprises an entropy source, the entropy source is implemented monolithically in a semiconductor substrate having a surface, the entropy source comprises a photon source,which is configured to emit photons when energized, the entropy source comprises a single-photon detector configured to detect the photons of the photon source and generate an entropy source output signal, the photon source is arranged between the surface of the semiconductor substrate and the single-photon detector, or the single-photon detector is arranged between the surface of the semiconductor substrate and the photon source, the photon source and the single-photon detector of the monolithic entropy source are arranged vertically one above the other, and the quantum random number generator comprises means for generating one or more quantum random numbers depending on the entropy source output signal.

2. Network according to claim 1, wherein at least two, preferably all, nodes of the plurality of nodes of the network are configured to use the random numbers generated by their respective quantum random number generator and / or another quantum random number generator in the network to generate cryptographic keys and initialization vectors (IVs).

3. Network according to claim 1 or 2, wherein at least two, preferably all, nodes of the plurality of nodes of the network are configured to use their respective random numbers and / or the random numbers of other nodes in the network to generate one-time passwords, OTPs, for the authentication of communication partners.

4. Network according to one of the preceding claims, wherein the network or wherein at least two, preferably all, nodes of the plurality of nodes of the network are configured to use their respective random numbers and / or the random numbers of other nodes in the network and / or random numbers in the network to support secure communication protocols such as TLS or IPsec.

5. Network according to one of the preceding claims, wherein the network or wherein at least two, preferably all, nodes of the plurality of nodes of the network are arranged to use their respective random numbers and / or the random numbers of other nodes in the network and / or random numbers in the network to carry out security protocols that ensure secure communication between the nodes.

6. Network according to one of the preceding claims, wherein the network or wherein at least two, preferably all, nodes of the plurality of nodes of the network are arranged to amplify and filter each random number generated by them by an entropy collection unit in order to avoid systematic errors or predictabilities.

7. A network according to any one of the preceding claims, wherein the network is configured to distribute the load of random number generation evenly across the nodes.

8. Network according to one of the preceding claims, wherein at least two, preferably all, nodes of the plurality of nodes of the network each comprise a security module configured to securely store the random numbers of the respective node and to use and / or keep them available for one or more different security-relevant applications.

9. Network according to one of the preceding claims, wherein at least two, preferably all, nodes of the plurality of nodes of the network each comprise a control device configured to store the random numbers in a protected memory area of ​​the control device of the respective node, which memory area can only be accessed by authorized processes in the network.

10. The network of claim 9, wherein the respective control devices are configured to detect anomalies in the random number generation and to perform corresponding recovery processes.

11. A network according to claim 9 or 10, wherein the respective control devices are configured to subject the generated random numbers to post-processing by techniques such as hashing or XOR-ing.

12. A network according to any one of the preceding claims, wherein the respective control devices are configured to use the random numbers to manage and use digital certificates required for authentication and establishing secure connections.

13. Network according to one of the preceding claims, wherein the network has computer- and / or machine-implemented mechanisms for error detection and recovery to ensure the functionality of the network even in the event of failure of individual nodes and / or failure of individual quantum random generators, for example by means of exchange of random numbers.

14. A network according to any one of the preceding claims, wherein the network is configured to prevent the use of unauthenticated vehicle or spare parts and / or software components by performing an authentication process upon installation or commissioning of such parts or components based on random numbers generated by the hardware-based quantum random number generators in the nodes of the network.

15. The network of claim 14, wherein the authentication process comprises the generation of a cryptographic key by the quantum random number generator of a node, which is then used to verify a digital certificate confirming the authenticity and integrity of the part or software component to be installed.

16. A network according to any one of the preceding claims, wherein the network is configured to detect compromise of one or more nodes by implementing an intrusion detection system (IDS) that continuously monitors random numbers of the hardware-based quantum random number generators of the nodes and identifies statistical anomalies in the random number generation that indicate compromise.

17. The network of claim 16, wherein the IDS performs a continuous entropy analysis of the random numbers generated by the quantum random number generators and sends an alarm message to a central control node in the vehicle network upon detected deviations from expected entropy values.

18. Network according to one of the preceding claims, wherein different cryptographic keys and / or encryption methods are used in the communication between different pairs of nodes of the network, which are dynamically selected and generated by the random numbers generated by the quantum random number generators.

19. The network of claim 20, wherein each node of the network is configured to use a unique combination of encryption methods and keys in each communication that differs from the combinations of other pairs of nodes.

20. A network according to any one of the preceding claims, wherein the network is configured to initiate a defensive behavior of one or more nodes when a compromise of one or more nodes is detected, by the affected nodes disconnecting themselves from communication in the network and reinitializing their quantum random number generators for an additional security check.

21. The network of claim 20, wherein the defensive behavior provides the affected nodes with the ability to perform a self-test to verify the integrity of the internal cryptographic keys and the random numbers generated by the quantum random number generator before the node is allowed to communicate with the network again.

22. Network according to one of the preceding claims, wherein the random numbers of the quantum random number generators are used to generate one-time passwords (OTPs) required for access to safety-critical functions of the vehicle, such as for unlocking control units or activating firmware updates.

23. A network according to any one of the preceding claims, wherein the network is configured such that upon detection of a potential threat from a compromise of a node or group of nodes, a redundant network protocol is activated which reroutes the communication paths within the network and secures the communication by dynamically generating new random numbers for encryption and authentication.

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