A quantum-accelerated lattice signature method and system for intelligent autonomous transportation systems

Abstract

This invention discloses a quantum-accelerated lattice signature method and system for intelligent autonomous transportation systems, belonging to the field of information security technology. The method includes inputting security parameters, a large prime modulus, a message to be signed, and user identity information into a computer system; constructing a random matrix over a finite field based on the security parameters and the large prime modulus, generating the kernel space minimum norm vector and trapdoor of this matrix via quantum circuits, and outputting system common parameters; extracting the private key based on the system common parameters and user identity information and storing it in qRAM, outputting the private key bound to the identity; converting the message to be signed into a bit vector embedding, using the private key to generate a short vector signature through quantum discrete Gaussian sampling, and binding a timestamp and link tag; verifying the short vector signature and determining the signature identity association using a hash chain structure; and finally updating the private key and outputting it. This invention aims to achieve efficient private key extraction, short vector signature generation, and improved system security for intelligent transportation systems.

Description

Technical Field

[0001] This invention belongs to the field of quantum cryptography and intelligent transportation information security technology, and relates to a secure signature scheme and system that combines quantum computing, lattice cryptography and identity authentication. Specifically, it relates to a quantum-accelerated lattice signature method and system for intelligent autonomous transportation systems. Background Technology

[0002] With the development of intelligent autonomous transportation systems, applications such as vehicle-to-everything (V2X), autonomous driving, and smart logistics have placed higher demands on the security of data transmission, the reliability of identity authentication, and the ability to trace information.

[0003] Traditional public-key cryptography based on number theory problems (such as RSA and elliptic curve cryptography) is vulnerable to efficient cracking by quantum computing technology, making it difficult to support the high security requirements of future intelligent transportation environments. Lattice cryptography, as an important branch of post-quantum cryptography, possesses the potential to resist quantum computing attacks due to its foundation in intractable problems such as the shortest vector problem (SVP) and the closest vector problem (CVP) on lattices, and has become one of the key research and promotion directions.

[0004] From the perspective of existing technological exploration, there are some practical applications in the field of integrating lattice cryptography and signature authentication in some public documents. For example, the invention patent application (CN202411448778.9) discloses a method and system for cross-domain authentication of fleets based on lattice cryptography and quantum random numbers. However, it still has bottlenecks in terms of signature length and computational efficiency, as well as the lack of dynamic key updates. The invention patent application (CN202211490943.8) discloses a method and device for multi-signature transactions in consortium blockchains based on lattice cryptography, but it does not optimize the storage overhead of signature length and also lacks a dynamic key update mechanism. Although the above existing technologies have made some explorations in lattice cryptography and quantum technology, they still have shortcomings in terms of signature efficiency and length optimization, and dynamic key update mechanisms, making it difficult to fully adapt to intelligent autonomous transportation systems.

[0005] In summary, existing lattice signature schemes still have shortcomings in practical applications, such as long signature lengths, low computational efficiency, and imperfect key update mechanisms, making it difficult to directly meet the real-time, dynamic, and traceability requirements of intelligent autonomous transportation systems. Furthermore, existing schemes often lack integration with quantum computing and quantum storage technologies (such as quantum random access memory qRAM), failing to fully leverage the potential advantages of quantum acceleration in key generation, signature generation, and authentication processes.

[0006] Therefore, there is an urgent need to design a new secure signature scheme that combines quantum computing and lattice cryptography to achieve efficient private key extraction, short vector signature generation, signature verification and dynamic key update, thereby providing intelligent autonomous transportation systems with authentication and data integrity guarantees that are resistant to quantum attacks. Summary of the Invention

[0007] The main objective of this invention is to provide a quantum-accelerated lattice signature method for intelligent autonomous transportation systems. This method combines quantum computing lattice cryptography with identity authentication mechanisms, and utilizes technologies such as quantum circuits to achieve efficient private key extraction, short vector signature generation, and improved system security for intelligent transportation systems.

[0008] Based on the first main aspect of the invention, the present invention provides a quantum-accelerated lattice signature method for intelligent autonomous transportation systems, comprising the following steps:

[0009] Input security parameters, the large prime number modulus q, the message to be signed, and user identity information into the computer system;

[0010] Based on the security parameters and the large prime modulus q, a random matrix is ​​constructed in a finite field. The kernel space minimum norm vector and trapdoor of the matrix are generated by a quantum circuit, and the common parameters of the system are output.

[0011] Based on the system's public parameters and the user's identity information, the private key is extracted through the Bernstein–Vazirani circuit and stored in qRAM, and the private key bound to the identity is output.

[0012] The message to be signed is converted into a bit vector embedding, and the private key is used to generate a short vector signature through quantum discrete Gaussian sampling and then bound with a timestamp and a link tag.

[0013] The hash chain structure is used to verify short vector signatures, and the QSVP determination mechanism is used to determine the signature identity association.

[0014] The private key is updated by combining a quantum pseudo-random function with a Merkle tree structure, and the updated private key is output.

[0015] In the information input into the computer system, security parameters are set by the key generation center (or system initialization module) according to post-quantum security requirements, such as the lattice cryptography security level recommended by NIST and other standards and technology research institutes. The large prime number modulus q is bound to the security parameters and generated together by the system initialization module. Messages to be signed include vehicle request data (such as license plate applications), real-time status (such as location), etc., which are input by the user through the in-vehicle terminal or automatically collected by the device. User identity information includes the vehicle owner's ID card and / or vehicle VIN code, which are entered into the system during registration.

[0016] As a further preferred embodiment, the construction of a random matrix over a finite field based on the security parameter and the large prime modulus q specifically involves generating a random matrix of the corresponding dimension over the finite field.

[0017] The generation of the kernel space minimum norm vector and trapdoor of the matrix via quantum circuitry specifically includes: applying a transformation to the orthonormal basis through QFT in the quantum circuitry, and combining the projection operator to find a vector that satisfies the condition that the product of the random matrix and the vector is 0 and that the norm of the vector is the minimum norm of all non-zero vectors in the kernel space; the trapdoor is generated by constructing a set of orthonormal bases in the kernel space.

[0018] As a further preferred embodiment, the step of basing the information on the public parameters and the user identity information specifically involves inputting the trapdoor and user identity identifier in the public parameters. The step of extracting the private key through the Bernstein-Vazirani circuit is to calculate the private key bound to the identity using the Bernstein-Vazirani circuit. The private key includes the trapdoor component bound to the identity and the initial hash chain value.

[0019] The qRAM storage refers to storing the trapdoor component in the private key that is bound to the identity using a quantum random access memory address-data mapping method.

[0020] When outputting the private key bound to the identity, a corresponding public key is generated simultaneously. The public key is generated by finite field operations on a random matrix and the trapdoor component bound to the identity, and finally, a key pair is output.

[0021] As a further preferred embodiment, the process of converting the message to be signed into a bit vector embedding involves splitting the message to be signed into a bit vector of a preset bit length, and embedding the bit vector into a matrix of the corresponding dimension through a message mapping matrix. The elements of this matrix are obtained by multiplying the bit vector elements by random elements in a finite field.

[0022] The process of generating a short vector by calling the private key through quantum discrete Gaussian sampling involves using the trapdoor component bound to the identity in the private key as input to the target matrix and generating the short vector through quantum discrete Gaussian sampling. The target matrix is ​​horizontally concatenated from a random matrix, a message mapping matrix, and a common perturbation matrix. The short vector satisfies the condition that the result of the finite field operation between the target matrix and the short vector is zero.

[0023] The link tag is generated by combining a non-zero small perturbation in a finite field with a hash function, and the final output is a signature containing the short vector, the link tag, and the timestamp.

[0024] As a further preferred embodiment, the signature verification using the hash chain structure is based on the hash function in the public parameters and the hash chain depth to reconstruct the target matrix and message mapping matrix, and to verify the signature congruence condition and norm condition. If both are satisfied, the verification is deemed successful; otherwise, the verification is deemed unsuccessful.

[0025] The congruence condition is that the result of the finite field operation between the target matrix and the short vector is zero, and the norm condition is that the vector norm does not exceed a preset threshold.

[0026] As a further preferred embodiment, the determination of signature identity association involves using the link tags corresponding to the two signatures to be determined and calculating the difference to construct a specific lattice structure composed of vectors that satisfy the condition that the finite field operation result of a random matrix and a vector is zero. The QSVP determination mechanism is used to detect whether the difference belongs to the lattice structure. If the finite field operation result of the random matrix and the vector is zero, it is determined that they come from the same identity; otherwise, it is determined that they come from different identities.

[0027] As a further preferred embodiment, the method of updating the private key by combining quantum pseudo-random functions and Merkle tree structures includes encoding the time period into a bit string, calling a pseudo-random function to generate key material for the current time period, using the key material as the leaf node of the Merkle tree, and constructing the intermediate nodes layer by layer through hash calculation to the root node of the Merkle tree; the updated key includes the key material, the Merkle root node, and the corresponding leaf node verification path.

[0028] As a further preferred embodiment, the quantum pseudo-random function is: ,in, It is a quantum pseudo-random function expression. Master key For a period of time, For the one-positive operator, It is a time period quantum state, This is an LWE security mapping, output result. This refers to the key material for that time period.

[0029] Based on the second main aspect of the present invention, a quantum-accelerated lattice signature system for intelligent autonomous transportation systems is provided, including a parameter generation module for generating common system parameters, including obtaining key vectors and trapdoors by processing random matrices through quantum circuits, and defining necessary mapping and sampling parameters.

[0030] The private key extraction module is used to combine quantum circuits and storage units to generate identity-bound key pairs, enabling private key storage and fast retrieval;

[0031] The signature generation module is used to convert messages into a specific matrix form, generate short vector signatures that satisfy norm constraints through quantum discrete Gaussian sampling, bind timestamps and link tags, and output signature results;

[0032] The verification module is used to reconstruct the message matrix by combining the hash chain structure, verify the congruence condition and norm condition of the signature, and output the verification result.

[0033] The identity recognition module is used to trace identity by comparing signature tags and using a quantum determination mechanism.

[0034] The private key update module is used to generate a new private key using hash chains and quantum random functions to ensure the security of the update.

[0035] The output of the parameter generation module is connected to the input of the private key extraction module, the signature generation module, the verification module, the identity recognition module, and the private key update module, respectively, to realize the transmission of common parameters.

[0036] Based on a third key aspect of the invention, the invention provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements a quantum-accelerated lattice signature method for intelligent autonomous transportation systems as described above.

[0037] Compared with existing technologies, this invention addresses the core pain points of existing lattice signature schemes, such as long signature lengths and low efficiency. To address these issues, this invention employs a triple-technology optimization: accelerating private key extraction through Bernstein–Vazirani quantum circuits; combining private key storage with qRAM, leveraging the quantum superposition advantage of qRAM to achieve fast private key retrieval and avoid retrieval delays associated with traditional storage media; and using quantum discrete Gaussian sampling to generate short vector signatures, significantly shortening the signature length while strictly controlling the signature vector norm, effectively meeting the high real-time requirements of intelligent autonomous transportation systems.

[0038] Secondly, existing signature schemes mostly focus on the unforgeability of signatures, but neglect the key requirements of signature integrity verification and identity traceability. This invention fills the gap in the identity traceability of existing technologies by adopting two schemes. First, a hash chain is used to verify the integrity of the signature. Second, a QSVP determination mechanism is combined to realize the identity association of the signature source. By analyzing the link tag association relationship of different signatures, the identity to which the signature belongs can be accurately located.

[0039] Finally, a dynamic private key update scheme is designed based on quantum pseudo-random functions and Merkle trees to ensure forward key security and avoid leakage risks. A unique key for each time period is generated using timestamps and related parameters, and the hierarchical hash structure of the Merkle tree is used to verify the consistency of key updates and ensure forward security. Simultaneously, relying on the quantum lattice resistance problem as a security foundation and deeply integrating with quantum technology, a suitable quantum-secure authentication and data integrity guarantee are provided for intelligent autonomous transportation systems. Attached Figure Description

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, obtaining other drawings based on these drawings without creative effort still falls within the scope of the present invention.

[0041] Figure 1 The following is an execution flowchart of a quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to one embodiment of the present invention;

[0042] Figure 2 This diagram illustrates a schematic of an intelligent autonomous transportation system according to an embodiment of the present invention.

[0043] Figure 3 This illustration shows a flowchart of a verification process between various ports / roles provided by an embodiment of the present invention. The diagram illustrates the signature and verification interaction process between the Client, Proxy, Signer, and Verifier ports.

[0044] Figure 4 The illustration shows a time-series diagram of a quantum computing tree (depth 4) for an intelligent autonomous transportation system provided by an embodiment of the present invention, demonstrating the Merkle tree structure and the hash chain implemented by the quantum resettable pseudo-random function (QPRF) for the time period t∈{0,1,…,15}. Detailed Implementation

[0045] The preferred embodiments of the present invention will be described in detail below to provide a clearer understanding of the purpose, features, and advantages of the invention. It should be understood that the following embodiments are not intended to limit the scope of the invention, but are merely illustrative of the essential spirit of the invention's technical solutions.

[0046] In the following description, certain specific details are set forth for the purpose of illustrating various disclosed embodiments in order to provide a thorough understanding of the various disclosed embodiments. However, those skilled in the art will recognize that the embodiments may be practiced without one or more of these specific details. In other instances, well-known techniques associated with the invention may not have been shown or described in detail to avoid unnecessarily obscuring the description of the embodiments.

[0047] Throughout this specification, references to "an embodiment" or "an embodiment" indicate that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment. Therefore, the appearance of "in an embodiment" or "an embodiment" in various places throughout the specification does not necessarily refer to the same embodiment. Furthermore, a particular feature, structure, or characteristic may be combined in any manner in one or more embodiments.

[0048] The specific meanings of the technical terms or English abbreviations that may be used in this invention are explained below:

[0049] Bernstein–Vazirani circuits are fundamental algorithmic circuits in quantum technology, specifically designed to solve the Bernstein–Vazirani problem (a decision problem demonstrating the advantages of quantum computing over classical computing). At its core, a hidden binary vector is determined through a single quantum query; essentially, it utilizes quantum superposition and interference effects to achieve efficient information extraction.

[0050] qRAM: qRAM (Quantum Random Access Memory) is the corresponding concept of classical RAM (Random Access Memory) in the field of quantum technology. It is a quantum storage device that can store and access quantum information. Its core function is to achieve efficient reading and writing operations on quantum information by encoding addresses and data through quantum states, while maintaining the superposition and parallelism unique to quantum computing.

[0051] Quantum Discrete Gaussian Sampling: A quantum algorithm that uses quantum computing to generate samples from a discrete Gaussian distribution of a lattice. Its core is to efficiently output lattice vectors that conform to a discrete Gaussian distribution with specific parameters through quantum circuits or quantum state operations, providing a key short vector generation tool for lattice cryptography.

[0052] QSVP Decision Mechanism: The QSVP decision mechanism (Quantum Shortest Vector Problem Decision Mechanism) is a quantum algorithm framework based on quantum computing technology to determine the "Shortest Vector Problem" (SVP) in a lattice. It is mainly used to determine whether there is a non-zero vector in the lattice with a length not exceeding a specific threshold. It is a core quantum tool in lattice cryptography for realizing functions such as identity association recognition and security verification.

[0053] Quantum pseudo-random functions (QPRFs) are an extension of classical pseudo-random functions (PRFs) in quantum computing scenarios. They are quantum functions that can be efficiently computed using quantum circuits, and whose output is indistinguishable from a truly random function from the perspective of a quantum attacker. Their core function is to generate pseudo-random outputs in a quantum environment, providing secure random numbers or key materials for quantum cryptography protocols.

[0054] Merkle tree structure: A tree-like data structure built on cryptographic hash functions. Its core function is to efficiently verify the integrity and consistency of large-scale data sets and support the rapid location of data tampering.

[0055] Bit vector element: A bit vector element is the basic unit that constitutes the data structure of a bit vector. Its essence is a single bit, which is the smallest information storage unit in a computer. It can only take the value 0 or 1 and has a clear ordered position in the bit vector.

[0056] Trapdoor components: Trapdoor components are the core building blocks of trapdoor mechanisms in cryptography; they are a set of specially structured information. Their core function is to allow the holder to efficiently solve a computational problem, while an attacker without the trapdoor finds it difficult to solve the problem in polynomial time. This is the core mechanism by which many cryptographic schemes achieve a balance between security and efficiency.

[0057] Random matrix: A type of matrix composed of random variables. Its core characteristic is that the elements at each position in the matrix are not fixed values, but random objects that follow a specific probability distribution. Therefore, the value of the entire matrix is ​​uncertain.

[0058] Message mapping matrix: A type of structured tool in cryptography used to convert raw messages (usually bit strings or data of arbitrary length) into a matrix form that can be processed by lattice cryptosystems. Its core function is to establish a mathematical relationship between the message and the lattice structure, enabling the message to participate in lattice operations.

[0059] Common perturbation matrix: In lattice cryptography, a common perturbation matrix is ​​a type of pre-generated, mutually accessible structured matrix. Its core function is to enhance system security by introducing "controllable random perturbation" while ensuring that the mathematical compatibility of the lattice cryptosystem is not compromised.

[0060] Link tags: A tag element used in markup languages ​​or document systems to create jumpable links. Its core function is to establish associations between different resources, allowing users to quickly jump to or trigger specific functions through click operations.

[0061] Hash function: A special mathematical function or algorithm whose core function is to map input data of arbitrary size to output data of fixed size.

[0062] Micro-perturbation r: refers to a deviation that is extremely small, quantifiable, and does not damage the core functions of the data, introduced into the original data technology in scenarios such as information processing, cryptography, or link generation in order to achieve goals such as collision resistance, tamper prevention, enhanced randomness, or protection of data privacy.

[0063] Hash chain: an ordered data structure built on cryptographic hash functions. Its core is to use the hash value of the previous data as the input of the next data to form a chain-like dependency relationship, which ultimately constitutes a string of immutable hash values ​​with a strict order. Essentially, it uses the one-wayness and collision resistance of hash functions to ensure the integrity and security of the chain.

[0064] Lattice structure: Lattice structure is a core concept at the intersection of algebraic structure and order structure in mathematics. Essentially, it is a partially ordered set that satisfies specific conditions of "minimum upper bound" and "maximum lower bound". It can also be transformed into an algebraic system with commutative, associative and absorption laws by defining binary operations.

[0065] Quantum circuits: Quantum circuits are the core abstract model of quantum computing, used to describe a series of ordered quantum operations performed on qubits, and are the basic framework for realizing quantum algorithms, quantum simulation and quantum information processing.

[0066] QFT: QFT (Quantum Fourier Transform) is the core transformation combining quantum mechanics and Fourier analysis. In essence, it is a unitary linear transformation defined on the Hilbert space composed of qubits. Its function is to transform the quantum state from the "computer representation" to the "frequency basis representation". It is the basic module of many core quantum algorithms.

[0067] Orthonormal basis: refers to a set of vectors that simultaneously satisfy "orthogonality" and "unit length", and any vector in space can be represented by this set of vectors.

[0068] Projection operators: a class of linear operators with the core property of "mapping a vector to a subspace, and the vector does not change after the mapping".

[0069] Kernel space: Kernel space is an important subspace closely related to linear transformations or matrices. Its core is the set of all original vectors that are mapped to the zero vector by a linear transformation.

[0070] LWE secure mapping: A cryptographic protocol that leverages the computational difficulty of the LWE problem (Learning with Errors) to enable one party to delegate the processing of encrypted data to another party using their secret key, thereby achieving secure key negotiation or ciphertext conversion.

[0071] like Figure 1As shown, in one feasible embodiment, an execution flowchart of a quantum-accelerated lattice signature method for intelligent autonomous transportation systems includes the following steps executed by a computer system:

[0072] S1, input security parameters, large prime number modulus q, message to be signed, and user identity information into the computer system;

[0073] S2, Based on the security parameters and the large prime modulus q, a random matrix is ​​constructed in a finite field, and the kernel space minimum norm vector and trapdoor of the matrix are generated by a quantum circuit, and the system common parameters are output.

[0074] In most feasible implementations, given a security parameter λ, a large prime modulus q is set, and operations are defined on a finite field Zq with dimension parameters n and m, and satisfying the following conditions: Given a message bit length of d and a hash chain depth of L, generate a random matrix in a finite field. In quantum circuits, the goal is to find the kernel space minimum norm vector of a random matrix A, i.e., to construct... ,satisfy And guarantee Minimum; of which Represents the kernel space vector. Let A represent the kernel space of matrix A.

[0075] Define the projection operator: and in quantum circuits, the standard orthogonal basis Apply QFT to get Let the decision function be... Find the space that satisfies the conditions after projection. of And construct a set of orthogonal bases. This serves as the basis for constructing trapdoors within the core space. , used to encode message μ into a matrix; where I is the identity matrix, For matrix The transpose of , QFT is the quantum Fourier transform. These are orthonormal basis vectors. It is a quantum state. is the standard deviation of Gaussian sampling.

[0076] Set the Gaussian sampling parameters: the standard deviation of Gaussian sampling is... The common disturbance matrix is and hash chain embedding matrix Finally, the common parameters are returned. .in For smoothing parameter functions, Let T be the norm of the trapdoor. It is a diagonal matrix construction operator. For message mapping matrix, d is The message bit length, where L is the depth of the hash chain.

[0077] S3, based on the public parameters and the user identity information, extract the private key through the Bernstein–Vazirani circuit and store it in qRAM, and output the private key bound to the identity;

[0078] In most feasible implementations, given the public parameters pp, identity id, random matrix A, and trapdoor T, it is possible to generate a private key based on identity using a quantum circuit and bind it to a hash chain structure, and then compute the id-bound private key using a Bernstein-Vazirani circuit. ,express By quantum pseudo-random function Based on identity Generate and store the private key using qRAM. This generates a binding public key. And generate the initial hash chain value. Finally, output the key pair. .in This is a hash function.

[0079] S4, the message to be signed is converted into a bit vector embedding, and the private key is used to generate a short vector signature through quantum discrete Gaussian sampling and bind a timestamp and a link tag;

[0080] In most feasible implementations, a short vector signature generation stage combining quantum discrete Gaussian sampling is used, given the public parameter pp, the message μ, and the updated private key. The hash chain depth L and timestamp t are used to split the message μ into a d-bit vector, i.e. and embed it into the matrix ;in, It is a message embedding matrix. These are components of the message mapping matrix. These are bit weighting coefficients.

[0081] Let each public key in the identity set L be... Concatenate them into an intermediate matrix Thus constructing the target matrix Calculate short vector signature Need to meet Its decision function is Bind quantum states to tags and calculate and generate link tags. , where r is a small perturbation, and output the signature. .in, This represents quantum discrete Gaussian sampling.

[0082] S5 uses a hash chain structure to verify the signature and uses the QSVP determination mechanism to determine the signature identity association.

[0083] In most feasible implementations, the algorithm verification process is as follows: Figure 3 As shown, given the public parameter pp, the message μ, and the public key... The depth L of the hash chain and the timestamp t are used to reconstruct the message matrix. ;

[0084] Simultaneously check whether the congruence condition and norm condition are satisfied, that is... and If both conditions are met, the visa verification is successful. Otherwise, the verification fails. Finally, return to... . For short vector signatures, N For identity set L The total number of public keys included.

[0085] QSVP is used to identify the identity association of the signature source. Given link tags tag1 and tag2, i.e. and , make a difference: And use QSVP for detection Is it in Span(P) that we set... Construct a judgment function If found If the condition is met, Link will output 1; otherwise, it will output 0. and For different tiny perturbations. This indicates the existence of a vector in the QSVP decision. Span(P) represents the column space of the hash chain embedding matrix P. Link is the signature identity association determination process.

[0086] S6 combines a quantum pseudo-random function with a Merkle tree structure to update the private key and outputs the updated private key.

[0087] In most feasible implementations, a dynamic private key update mechanism, given a public parameter pp, a timestamp t, and an initial hash chain value sht, updates the private key in each time period, thus ensuring forward security.

[0088] like Figure 4 As shown, the current time period Encoded bit string format: and define the QPRF function. ,in, It is a quantum pseudo-random function expression. Master key For a period of time, For the one-positive operator, It is a time period quantum state, This is an LWE security mapping, output result. This refers to the key material for that time period.

[0089] Use x t Construct a Merkle tree, with leaf nodes as The intermediate node is Iterate layer by layer until you obtain: Used for key confirmation and consistency verification of the verification chain. The pseudo-random key corresponding to time period t is output as the key for the current time period. And output the path verification at the same time. and . This represents the verification path for the t-th time period. This represents the root node of the Merkle tree. This represents the hash value of the root node.

[0090] like Figure 2 As shown in the figure, the present invention provides a schematic diagram of a quantum accelerated lattice signature scheme for intelligent autonomous transportation system, which illustrates the overall process of the present invention: the vehicle owner first inputs identity information, generates a public key and private key pair bound to the identity, and initiates a license plate and other information application request through the on-board unit (OBU).

[0091] At the same time, a signature is generated for the requested data. The vehicle signature request is uploaded to the vehicle network service provider, which verifies the signature. Once verified, the signature is stored in the cloud server and a historical signature list is generated for periodic inspection. When needed, the traffic management department can retrieve and verify the signature from the cloud server, effectively confirming the legality of the vehicle's identity and enabling traceable supervision, thus ensuring the integrity and security of vehicle information transmission in the intelligent connected environment.

[0092] like Figure 3 The diagram shown is a flowchart of a verification process between various ports / roles provided in an embodiment of the present invention, illustrating the signing and verification interaction process between the Client, Proxy, Signer and Verifier ports: The Client first initiates a connection through the Proxy to request the system's public parameters; the Proxy interacts with the Signer to obtain the required public parameters and then returns them to the Client.

[0093] The client inputs a message requiring signature in a loop, which is then forwarded to the signer via a proxy, requesting a signature. The signer signs the message according to common parameters and returns the signature result to the client via the proxy. Finally, the signature result is forwarded by the client or proxy to the verifier, who verifies the legality of the signature, ensuring the integrity of the message and the validity of the signature, thereby realizing a secure verification process between all participating parties in the system.

[0094] The technical terms, principles, or means related to the technical solutions of the present invention mentioned in the above embodiments, which are not described in detail above, are all well-known technologies or common practices that are known to those skilled in the art.

[0095] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A quantum-accelerated lattice signature method for intelligent autonomous transportation systems, characterized in that, Includes the following steps, Input security parameters, the large prime number modulus q, the message to be signed, and user identity information into the computer system; Based on the security parameters and the large prime modulus q, a random matrix is ​​constructed in a finite field. The kernel space minimum norm vector and trapdoor of the matrix are generated by a quantum circuit, and the common parameters of the system are output. Based on the system's public parameters and the user's identity information, the private key is extracted through the Bernstein–Vazirani circuit and stored in qRAM, and the private key bound to the identity is output. The message to be signed is converted into a bit vector embedding, and a short vector signature is generated by quantum discrete Gaussian sampling using the private key and then bound with a timestamp and a link tag. The hash chain structure is used to verify short vector signatures, and the quantum shortest vector problem determination mechanism is used to determine the signature identity association. The private key is updated by combining a quantum pseudo-random function with a Merkle tree structure, and the updated private key is output. The method of updating the private key by combining quantum pseudo-random functions and Merkle tree structure includes encoding the time period into a bit string, calling a pseudo-random function to generate key material for the current time period, using the key material as the leaf node of the Merkle tree, and constructing the intermediate nodes layer by layer through hash calculation to the root node of the Merkle tree; the updated key includes the key material, the Merkle root node, and the corresponding leaf node verification path. The quantum pseudo-random function is: ,in, It is a quantum pseudo-random function expression. Master key For a period of time, For the one-positive operator, It is a time period quantum state, This is an LWE security mapping, output result. This refers to the key material for that time period.

2. The quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to claim 1, characterized in that, The construction of a random matrix over a finite field based on the security parameter and the large prime modulus q specifically involves generating a random matrix of the corresponding dimension over the finite field. The generation of the kernel space minimum norm vector and trapdoor of the matrix via quantum circuitry specifically includes: applying a transformation to the orthonormal basis through QFT in the quantum circuitry; combining the projection operator to find a vector that satisfies the condition that the product of the random matrix and the kernel space minimum norm vector is 0, and the norm of the vector with a product of 0 is the minimum norm of all non-zero vectors in the kernel space; the trapdoor is generated by constructing a set of orthonormal bases in the kernel space.

3. The quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to claim 1, characterized in that, The step of basing the system public parameters and the user identity information on inputting the trapdoor and user identity identifier from the system public parameters, and extracting the private key through the Bernstein-Vazirani circuit, which calculates the private key bound to the identity using the Bernstein-Vazirani circuit; the private key includes the trapdoor component bound to the identity and the initial hash chain value. The qRAM storage refers to storing the trapdoor component in the private key that is bound to the identity using a quantum random access memory address-data mapping method. When outputting the private key bound to the identity, a corresponding public key is generated simultaneously. The public key is generated by finite field operations on a random matrix and the trapdoor component bound to the identity, and finally, a key pair is output.

4. The quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to claim 1, characterized in that, The process of converting the message to be signed into a bit vector embedding involves splitting the message to be signed into a bit vector of a preset bit length, and embedding the bit vector into a matrix of the corresponding dimension through a message mapping matrix. The elements of this matrix are obtained by multiplying the bit vector elements by random elements in a finite field. The process of generating a short vector by calling the private key through quantum discrete Gaussian sampling involves using the trapdoor component bound to the identity in the private key as input to the target matrix and generating the short vector through quantum discrete Gaussian sampling. The target matrix is ​​horizontally concatenated from a random matrix, a message mapping matrix, and a common perturbation matrix. The short vector satisfies the condition that the result of a finite field operation between the target matrix and the short vector is zero. The link tag is generated by combining a non-zero small perturbation in a finite field with a hash function, and the final output is a signature containing the short vector, the link tag, and the timestamp.

5. The quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to claim 4, characterized in that, The verification of short vector signatures using the hash chain structure is based on the reconstruction of the target matrix and message mapping matrix using the hash function and hash chain depth in the system's public parameters. The signature congruence condition and norm condition are verified. If both are satisfied, the verification is deemed successful; otherwise, the verification is deemed unsuccessful. The congruence condition is that the result of the finite field operation between the target matrix and the short vector is zero, and the norm condition is that the vector norm does not exceed a preset threshold.

6. The quantum-accelerated lattice signature method for intelligent autonomous transportation systems according to claim 1 or 5, characterized in that, The process of determining the association between signature identities involves using the link tags corresponding to the two signatures to be determined and calculating the difference. A specific lattice structure is constructed, consisting of vectors whose finite field operation result of a random matrix and a vector is zero. The quantum shortest vector problem determination mechanism is used to detect whether the difference belongs to this lattice structure. If the finite field operation result of the random matrix and the vector is zero, it is determined that they come from the same identity; otherwise, they are determined to come from different identities.

7. A quantum-accelerated lattice signature system for implementing the method of any one of claims 1-6 for intelligent autonomous transportation systems, characterized in that, It includes a parameter generation module for generating common system parameters, including obtaining key vectors and trapdoors by processing random matrices through quantum circuits, and defining necessary mapping and sampling parameters; The private key extraction module is used to combine quantum circuits and storage units to generate identity-bound key pairs, enabling private key storage and fast retrieval; The signature generation module is used to convert messages into a specific matrix form, generate short vector signatures that satisfy norm constraints through quantum discrete Gaussian sampling, bind timestamps and link tags, and output signature results; The verification module is used to reconstruct the message matrix by combining the hash chain structure, verify the congruence condition and norm condition of the signature, and output the verification result. The identity recognition module is used to trace identity by comparing signature tags and using the quantum shortest vector problem determination mechanism; The private key update module is used to generate a new private key using hash chains and quantum random functions to ensure the security of the update. The output of the parameter generation module is connected to the input of the private key extraction module, the signature generation module, the verification module, the identity recognition module, and the private key update module, respectively, to realize the transmission of system public parameters.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the quantum-accelerated lattice signature method for intelligent autonomous transportation systems as described in any one of claims 1-6.

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