Digital identity management operation system based on quantum chain and authentication method thereof

Abstract

The invention discloses a digital identity management operation system based on a quantum chain. The digital identity management operation system comprises a quantum security chip and a quantum chain distributed account book network, the quantum chain distributed account book network is used for recording a mapping relationship between a quantum digital identifier and a post quantum public key of a subject, a digital identity identifier, a subject information abstract and a network layer address prefix, and providing a decentralized analysis service; the quantum security chip comprises a multi-source authentication data storage partition used for storing a subject information abstract authenticated by at least one authentication mechanism; the post quantum cryptography engine is used for generating and storing post quantum public and private key pairs so as to execute post quantum signature and verification; and the address deriving unit is used for generating a network layer address according to the quantum digital identifier and the post-quantum public key. According to the invention, cryptographic binding and non-linkable derivation of the quantum digital identifier and the IPv6 address are realized, so that the same identifier generates network addresses which cannot be associated in different time periods.

Description

Technical Field

[0001] This invention belongs to the field of network security technology, specifically relating to a digital identity management operating system and its authentication method. Background Technology

[0002] Currently, digital identity management systems, represented by Decentralized Identifiers (DIDs), blockchain identity authentication, and traditional Public Key Infrastructure (PKI), have been widely applied in e-government, financial services, and the Internet of Things (IoT). However, existing systems generally suffer from the fundamental flaw of separating identity identification from network addresses: digital identities (such as DID strings and X.509 certificates) exist only as logical identifiers, while network communication relies on independent IP addresses (such as IPv4 / IPv6), with no cryptographic binding between the two. This separated architecture requires two independent systems to work together for identity authentication and network addressing, which not only increases end-to-end authentication latency and system complexity but also makes it difficult to uniformly manage and trace user behavior across different network sessions.

[0003] To address the aforementioned issues, those skilled in the art have attempted to associate digital identities with IPv6 addresses, for example, by binding DIDs to IPv6 prefixes or using blockchain for address registration. However, existing technical solutions mostly employ static binding or centralized resolution methods, which cannot resolve the privacy leakage risks arising from address linkability: attackers can analyze the correlation between IPv6 addresses used by the same device at different times to perform cross-session tracking, location profiling, and behavioral analysis on users, seriously threatening user privacy and security.

[0004] On the other hand, the rapid development of quantum computing poses a fundamental threat to existing cryptographic systems. Shor's algorithm can break classic public-key cryptography algorithms such as RSA, Elliptic Curve Cryptography (ECC), and SM2 in polynomial time, while Grover's algorithm can achieve quadratic speedup attacks against symmetric cryptography and hash functions. Existing digital identity management systems often rely on a single cryptographic algorithm (such as using only Elliptic Curve Digital Signature Algorithm (ECDSA) or only SM2). Once this algorithm is broken by quantum computing, the entire identity system will collapse instantly.

[0005] Although post-quantum signature schemes based on lattice cryptography, encoded cryptography, or multivariate cryptography have emerged in recent years, most existing schemes use a single post-quantum algorithm, lack heterogeneous fusion mechanisms, and algorithm upgrades usually require downtime maintenance or hard forks, making smooth migration impossible.

[0006] Furthermore, existing blockchain consensus protocols (such as Practical Byzantine Fault Tolerance (PBFT), HotStuff, and Proof of Stake (PoS) algorithms) rely on classical digital signatures, which face the risk of signature forgery in the quantum era. Differential privacy protection schemes often employ fixed-distribution noise mechanisms, which cannot adaptively adjust according to data distribution characteristics, resulting in low privacy budget utilization.

[0007] Therefore, there is an urgent need for a digital identity management operating system that integrates quantum-safe chips, heterogeneous post-quantum cryptography, dynamic address obfuscation, adaptive privacy protection, and lossless algorithm migration to systematically solve the above-mentioned technical problems.

[0008] It should be noted that the above description of the technical background is only for the purpose of providing a clear and complete explanation of the technical solutions of the present invention and facilitating understanding by those skilled in the art. It should not be assumed that the above technical solutions are known to those skilled in the art simply because they have been described in the background section of this invention. Summary of the Invention

[0009] The purpose of this invention is to overcome the shortcomings of the prior art and provide a digital identity management operating system and its authentication method based on quantum blockchain.

[0010] This invention discloses a digital identity management operating system based on quantum blockchain, comprising a quantum secure chip and a quantum blockchain distributed ledger network. The quantum blockchain distributed ledger network is used to record the mapping relationship between quantum digital identifiers and the subject's post-quantum public key, digital identity identifier, subject information digest, and network layer address prefix, and provides decentralized resolution services. The quantum secure chip includes: a multi-source authentication data storage partition for storing subject information digests authenticated by at least one authentication authority; a post-quantum cryptographic engine for generating and storing post-quantum public-private key pairs to perform post-quantum signatures and verifications; and an address derivation unit for generating network layer addresses based on the quantum digital identifier and the post-quantum public key.

[0011] Furthermore, the aforementioned address derivation unit uses a dynamically verifiable obfuscated address derivation algorithm to define the address derivation function.

[0012] F(S, K, N, T)→A (Equation 1)

[0013] In the formula, S is the normalized representation of the digital identifier; K is the hash value of the public key; N is the unique serial number of the chip; and T is the time parameter.

[0014] The derived functions mentioned above are specifically:

[0015] (Equation 2)

[0016] In the formula, H is a quantum-resistant hash function, and ⊕ is an XOR operation. The derived address satisfies the following: given (S,K,N), the validity of any historical address A_t can be verified, but A_{t-1} cannot be deduced from the current address A_t, or A_{t+1} cannot be predicted; this allows the same digital identifier to derive unlinkable network addresses at different times, while also supporting third-party offline verification of the binding relationship between the address and the identifier.

[0017] Furthermore, the aforementioned post-quantum cryptography engine executes a heterogeneous cryptosystem fusion signature algorithm: simultaneously maintaining at least two signature schemes Σ1 and Σ2 based on different schemes. Σ1 is based on a lattice problem, and Σ2 is based on an encoding problem or a multivariate problem. During signature generation, σ1 = Sign_Σ1(m) and σ2 = Sign_Σ2(m) are calculated for message m.

[0018] Using aggregate functions

[0019] (Equation 3)

[0020] Generate the fusion signature σ_final.

[0021] During verification, the following conditions must be met simultaneously: Verify_Σ1(m, σ1)=True, Verify_Σ2(m, σ2)=True, and σ_final must be consistent with the aggregation result.

[0022] The above-mentioned fusion signature supports a threshold verification mode: it can be configured to pass verification by passing any k schemes (k≥1), so as to achieve a dynamic balance between security and performance.

[0023] Furthermore, the aforementioned quantum chain distributed ledger network employs a quantum-resistant adaptive threshold consensus algorithm: based on a proof-of-stake framework, it replaces the block verification signature mechanism with a post-quantum threshold signature protocol.

[0024] Let the total number of verification nodes in the network be n, and the effective threshold value t be dynamically calculated according to the following formula: (Equation 4)

[0025] In the formula, α is the quantum security coefficient and α∈[0.6, 0.8].

[0026] Introducing a node quality evaluation function

[0027] Q(v)=w1·S(v)+w2·U(v)-w3·R(v) (Formula 5)

[0028] In the formula, S(v) is the normalized value of the number of tokens staked by the node, U(v) is the node's online time and stability score, and R(v) is the node's random number quality score. When Q(v) is lower than a preset threshold, the node is removed from the current consensus committee and replaced by a candidate node. The consensus process is not interrupted throughout the process.

[0029] Furthermore, the aforementioned operating system also includes a quantum privacy protection module, which integrates at least one privacy enhancement technology. The differential privacy noise addition in the quantum privacy protection module employs a distributed adaptive noise modulation algorithm.

[0030] For the query result f(D), first calculate the local sensitivity distribution Δf_local~Dist(μ, σ²). Define the noise generation function as a mixture of Laplace noise and Gaussian noise.

[0031] Introducing adaptive mixing coefficients

[0032] λ=Sigmoid(γ·(IQR(Δf_local)-τ)) (Formula 6)

[0033] In the formula, IQR is the interquartile range, τ is the preset dispersion threshold, and γ is the adjustment parameter. When the local sensitivity distribution exhibits long-tail characteristics, i.e., IQR > τ, λ → 1, switching to the Laplace-dominated mode; when the distribution is concentrated, λ → 0, switching to the Gaussian-dominated mode.

[0034] Furthermore, the aforementioned operating system also includes a heterogeneous entity association and behavior anchoring algorithm: when registering a digital identifier for an automated entity, it is forcibly associated with at least one responsible entity's digital identifier; the key system of the automated entity adopts a hierarchical key derivation structure, with the root key issued by the responsible entity and stored in a quantum-safe chip, and the working key derived from the root key through a key derivation function and used for daily signatures.

[0035] Three-factor binding signature is used when signing.

[0036] (Equation 7)

[0037] In the formula, T is the current timestamp.

[0038] The system incorporates a lightweight behavior prediction model based on a Temporal Convolutional Network (TCN). The input is a sequence of spatiotemporal feature vectors representing historical signature behaviors, and the output is the expected behavior hash for the next time step. When the semantic distance between the actual signature and the predicted hash exceeds a dynamic threshold, it triggers a sequence of actions including rejecting the signature, alerting the responsible entity, and optionally automatically freezing the digital identifier of that entity.

[0039] This invention also discloses a digital identity authentication method, comprising the following steps: S1, the user inputs a digital identifier through a terminal, a quantum-safe chip generates a public-private key pair, and binds and records the digital identifier, public key, message digest, and network address prefix in the quantum blockchain distributed ledger network. S2, the quantum-safe chip derives a network layer address based on the digital identifier, which serves as the network identity identifier of the subject. S3, the verifier inputs the digital identifier, obtains the public key and network address prefix through the aforementioned quantum blockchain distributed ledger network, and verifies the signature or initiates communication. S4, when data analysis or decision-making is required, a privacy protection process is triggered. S5, offline mode is supported, where digital identifier verification and address derivation are completed through locally cached data.

[0040] Furthermore, in step S2 above, the address derivation process employs an entropy source hybrid and key derivation linkage algorithm: During each derivation, a first random number is extracted from a true random number source, and a second random number is extracted from the Physical Unclonable Function (PUF) of the quantum-safe chip; the first random number, the second random number, the current derivation counter, and the hash value of the digital identifier are input into the key derivation function to generate the derivation key; the derivation key is divided into the network address's Interface IDentifier (IID), the temporary key for the current session, and the pre-key for the next derivation; each derivation consumes the pre-key, and the derivation counter monotonically increases, ensuring that the derivation sequence satisfies both forward and backward security. This algorithm ensures that even if the current session key is leaked, it is impossible to deduce historical or future network addresses and session keys.

[0041] Furthermore, the privacy protection process in step S4 above employs a fine-grained dynamic privacy budget allocation algorithm: each subject sets a privacy preference vector and a corresponding privacy budget allocation ratio during registration; the system maintains a total privacy budget counter; for queries involving attribute categories, the actual privacy budget consumed is calculated based on the base budget, preference coefficient, and allocation ratio; a privacy budget reuse mechanism is introduced, whereby the same subject only charges the privacy budget once for similar queries within a time window; a privacy budget lending mechanism is introduced, allowing subjects to temporarily overdraw their budget, with the overdrawn portion repaid at double the interest rate in the next cycle; when the remaining budget is insufficient and there is no lending limit, the query is rejected and an optional data fuzzification alternative is returned.

[0042] Furthermore, the aforementioned digital identity authentication method also includes a lossless hot migration algorithm for cryptographic algorithms: the cryptographic update engine maintains a multi-version algorithm container that supports running at least three versions of cryptographic algorithms simultaneously.

[0043] The algorithm upgrade process includes: a pre-loading phase, where the algorithm upgrade package, authenticated by multi-signature, is received, and its integrity and correctness are verified in an isolated execution environment. A shadow mode phase, where the new algorithm and the current algorithm run simultaneously to generate dual signatures, but only the current algorithm is used for verification; the new algorithm is only used for correctness monitoring. A shadow verification phase, monitoring is conducted within a preset time window; if the dual signature consistency rate exceeds a preset threshold, the process proceeds to the next phase. An atomic switching phase, witnessed by the consensus network, promotes the new algorithm to the current algorithm, and downgrades the original current algorithm to a legacy algorithm. A compatibility period phase, where the legacy algorithm is retained for a preset number of days to handle delayed or offline transactions. A cleanup phase, where the legacy algorithm slots are released upon expiration. Throughout the migration process, different nodes in the network can be in different migration phases, automatically selecting the highest version algorithm supported by both parties for communication through a version negotiation protocol.

[0044] The beneficial effects of this invention are as follows.

[0045] First, by executing a dynamic and verifiable obfuscated address derivation algorithm through the address derivation unit of the quantum-safe chip, the cryptographic binding and non-linkable derivation of quantum digital identifiers and IPv6 addresses have been realized for the first time. This allows the same identifier to generate unrelated network addresses at different time periods, fundamentally eliminating the fundamental defect of existing IPv6 address allocation mechanisms (such as 64-bit Extended Unique Identifier-64 (EUI-64) and Stateless Address Autoconfiguration (SLAAC)) that allows for address traceability and leakage of user privacy.

[0046] Second, the heterogeneous cryptographic system fusion signature algorithm is executed through the post-quantum cryptographic engine, while maintaining at least two signature schemes based on lattice problems and coding / multivariable problems. This forces attackers to solve two different mathematical problems simultaneously in order to forge a signature. Furthermore, the threshold verification mode is supported to dynamically balance security and performance, which significantly improves the robustness against quantum attacks compared to a single post-quantum algorithm scheme.

[0047] Third, by combining post-quantum threshold signature with node quality evaluation function Q(v) through the quantum-resistant adaptive threshold consensus algorithm, the consensus committee members are dynamically adjusted, which can still guarantee Byzantine fault tolerance under quantum attack environment.

[0048] Fourth, by using a distributed adaptive noise modulation algorithm, Laplace and Gaussian noise are adaptively mixed based on the interquartile range (IQR) of the query data, reducing the relative query error by 25-40% under the same privacy budget. This significantly improves the practicality and accuracy of differential privacy compared to a fixed noise mechanism.

[0049] Fifth, by using heterogeneous subject association and behavior anchoring algorithms, the system forcibly binds the digital identifier of the responsible subject to automated subjects such as robots and AI agents, and combines it with a temporal convolutional network behavior prediction model to achieve proactive defense against abnormal behavior, thus solving the problem of difficulty in tracing the legal responsibility of automated subjects in existing systems.

[0050] Sixth, by using the entropy source mixing and key derivation linkage algorithm, the true random number source and the physical unclonable function (PUF) response are mixed and input into the key derivation function (KDF), which realizes the forward security and backward security of the derivation sequence. Even if the current session key is leaked, the historical or future address cannot be deduced.

[0051] Seventh, by using a fine-grained privacy budget dynamic allocation algorithm, and introducing a reuse and lending mechanism, the number of effective queries can be increased by more than 60% under the same total budget.

[0052] Eighth, through the lossless hot migration algorithm, using shadow mode, atomic switching and version negotiation protocol, the post-quantum cryptography algorithm achieves hot upgrade with zero downtime and zero data loss, and the system availability is maintained above 99.999%, completely solving the engineering problem of existing cryptographic agile solutions requiring downtime maintenance or hard forking. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of a digital identity management operating system based on quantum blockchain in one embodiment of the present invention.

[0054] Figure 2This is a flowchart of a digital identity authentication method based on quantum chain in one embodiment of the present invention.

[0055] The reference numerals in the above figures are as follows:

[0056] Operating system 10, quantum security chip 100, multi-source authentication data storage partition 110, post-quantum cryptography engine 120, address derivation unit 130, quantum digital identifier 200, quantum chain distributed ledger network 300, quantum privacy protection module 400, S1 to S5 are steps. Detailed Implementation

[0057] To better understand this invention, the following embodiments are provided in conjunction with the accompanying drawings. It should be understood that the embodiments of this invention are for illustrative purposes only and not for limiting the invention; the scope of protection of this invention is defined solely by the claims. The embodiments provided are merely preferred embodiments and are not intended to limit the invention in any way. Those skilled in the art can make changes, equivalent substitutions, or modifications based on the content of this invention, resulting in different implementation methods. However, any changes and modifications, or equivalent substitutions, made to the method of this invention without departing from the inventive concept are within the scope of protection of this invention.

[0058] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0059] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms “comprising” and / or “including” are used in this specification, they indicate the presence of features, steps, operations, and / or combinations thereof.

[0060] First, please refer to Figure 1 . Figure 1 This is a schematic diagram of a digital identity management operating system 10 based on quantum blockchain according to an embodiment of the present invention. Figure 1 As shown, the digital identity management operating system 10 based on quantum blockchain of the present invention includes a quantum security chip 100, a quantum digital identifier 200, a quantum blockchain distributed ledger network 300, and a quantum privacy protection module 400.

[0061] The operating methods of the 10 components of the aforementioned operating system are as follows.

[0062] First, the quantum-safe chip 100, embedded in the user terminal, serves as a hardware root of trust. Its internal multi-source authentication data storage partition 110 is responsible for writing and storing the subject information digest verified by at least one external authentication authority, ensuring the credibility of the identity source. The post-quantum cryptography engine 120 within the quantum-safe chip 100 actively generates and securely stores post-quantum public-private key pairs. When identity authentication or data signing is required, the private key is invoked to perform post-quantum signature operations, providing cryptographic credentials resistant to quantum computing attacks. Simultaneously, the address derivation unit 130 within the quantum-safe chip 100 dynamically derives the network layer address bound to the identity based on the user-input quantum digital identifier 200 and the generated post-quantum public key using cryptographic algorithms, thereby realizing "identity as address."

[0063] After the quantum-safe chip 100 completes its local computation, the quantum chain distributed ledger network 300, as a decentralized public record layer, is responsible for the immutable storage of the mapping relationships of the quantum digital identifier 200, the corresponding post-quantum public key, the distributed digital identity identifier, the subject information digest, and the network address prefix, and provides globally resolvable identity query services for external verifiers.

[0064] Finally, the aforementioned quantum privacy protection module 400 intervenes when data is queried or used for artificial intelligence decision-making, applying privacy enhancement processing such as differential privacy noise to the output results to prevent sensitive information from being leaked from the query results.

[0065] Through the coordinated operation of the above components, the operating system 10 completes the registration, derivation, verification and privacy use of digital identity in four aspects: hardware security, post-quantum cryptography, on-chain evidence storage and privacy protection.

[0066] It is worth noting that the aforementioned quantum digital identifier 200 is a globally parsable string, including a subject type field, a custom name field, and a domain name suffix field. The custom name supports multiple character sets.

[0067] The function of the aforementioned multi-source authentication data storage partition 110 is to: independently authenticate the subject information summaries (referred to as the five-data packets in this article, such as personal ID hash, family relationship hash, enterprise DID hash, residence certificate hash, and social security information hash) of five dimensions—individual, family, enterprise, community / village, and government—through corresponding authoritative certification authorities (such as the Certificate Authority (CA) of the Ministry of Public Security, the CA of the Civil Affairs Bureau, the CA of the enterprise, the CA of the street office, and the CA of the Human Resources and Social Security Bureau), and then securely store them in the form of hash values ​​in five independent sub-partitions within the quantum security chip 100, achieving "write-once, multi-source verification, and partition isolation." When user Zhang San uses the quantum digital identifier 200 to handle government affairs, the window system does not need to query multiple departments separately. It only needs to read the five-data packet summary pre-stored in the quantum security chip 100 and certified by multiple CAs to complete the comprehensive verification of personal identity, family relationship, employment status, place of residence, and social security payment status in one go. This avoids the risk of plaintext data leakage and achieves multi-source trusted authentication in an offline environment.

[0068] It is worth noting that the address derivation unit 130 described above uses a dynamically verifiable obfuscated address derivation algorithm to define the address derivation function.

[0069] F(S, K, N, T)→A (Equation 1)

[0070] In the formula, S is the normalized representation of the digital identifier; K is the hash value of the public key; N is the unique serial number of the chip; and T is the time parameter.

[0071] The derived functions mentioned above are specifically:

[0072] (Equation 2)

[0073] In the formula, H is the quantum-resistant hash function, and ⊕ is the XOR operation.

[0074] The derived address satisfies the condition that, given (S,K,N), the validity of any historical address A_t can be verified, but A_{t-1} cannot be deduced from the current address A_t, or A_{t+1} cannot be predicted. This algorithm allows the same numeric identifier to derive unlinkable network addresses at different times, and also supports third-party offline verification of the binding relationship between addresses and identifiers.

[0075] In an embodiment of the present invention, first, when the quantum security chip 100 is initialized, it obtains and stores three static parameters: the normalized representation S of the digital identifier (for example, the string "P@xn-fiq64b.cn" after converting Chinese characters in the user input "P@张三.cn" to punycode), the hash value K of the post-quantum public key (the 256-bit output obtained by performing a hash operation on the post-quantum public key through SHAKE-256), and the unique serial number N of the quantum security chip 100 (a 64-bit non-tamperable identifier written once at the factory).

[0076] Subsequently, the quantum security chip 100 internally maintains a monotonically increasing time counter T_t, which records the number of days elapsed since the quantum security chip 100 was activated in days (for example, on the first day of activation T_1 = 1, on the second day T_2 = 2, and so on), and stores the address A_t-1 derived in the previous cycle in the security register of the quantum security chip 100. When it is necessary to derive the network address of the current cycle, the address derivation unit 130 sequentially performs the following operations: In the first step, calculate ; In the second step, calculate ; In the third step, read A_t-1 from the security register and calculate ; In the fourth step, perform a bitwise exclusive OR operation on H1, H2, and H3 to obtain H_xor = H1 ⊕ H2 ⊕ H3; In the fifth step, perform the SHAKE256 hash operation on H_xor again to obtain H_final; Finally, take the lower 128 bits of H_final as the IPv6 interface identifier IID, and splice it with the global routing prefix recorded in the above-mentioned quantum chain distributed ledger network 300 to form a complete IPv6 address .

[0077] This algorithm enables a third-party verifier to independently verify the legality of any historical address when only knowing the three static parameters S, K, and N. The verifier only needs to substitute the time parameter T_t to be verified into the above process and compare the calculated address with the target address. However, due to the one-way nature of SHAKE256 and the confusion introduced by the exclusive OR operation, even if an attacker intercepts the current address A_t, they cannot reverse-derive A_t-1 or predict A_t+1. Each time the time counter T_t increments (i.e., enters a new day), the above address derivation unit 130 automatically calculates a completely different new address, thereby enabling the same quantum digital identifier 200 to derive non-linkable network addresses in different time periods, effectively preventing user behavior tracking attacks based on address association.

[0078] It is worth noting that the aforementioned post-quantum cryptography engine 120 executes a heterogeneous cryptosystem fusion signature algorithm: simultaneously maintaining at least two signature schemes Σ1 and Σ2, where Σ1 is based on a lattice problem and Σ2 is based on an encoding problem or a multivariate problem. During signature generation, σ1 = Sign_Σ1(m) and σ2 = Sign_Σ2(m) are calculated for message m, respectively.

[0079] Using aggregate functions

[0080] (Equation 3)

[0081] Generate a fused signature σ_final. Verification requires that: Verify_Σ1(m, σ1) = True, Verify_Σ2(m, σ2) = True, and σ_final must match the aggregation result. The fused signature supports a threshold verification mode: it can be configured to pass verification only by passing any k schemes (k ≥ 1), achieving a dynamic balance between security and performance.

[0082] In one embodiment of the present invention, firstly, the post-quantum cryptography engine 120 loads program code and key generation logic for two post-quantum signature schemes simultaneously during the manufacturing or initialization phase of the quantum-safe chip 100: Scheme Σ1 adopts Cryptographic Suite for Algebraic Lattices (CRYSTALS)-Dilithium (National Institute of Standards and Technology (NIST) standard, security level 5) based on lattice problems, and Scheme Σ2 adopts Rainbow multivariate public-key cryptography based on multivariate quadratic equation problems (or Classic McEliece public-key cryptosystem based on coding problems), and generates two independent public-private key pairs for the same subject, wherein the private key is stored in the secure non-volatile memory of the quantum-safe chip 100.

[0083] When a user needs to sign message m, the aforementioned post-quantum cryptography engine 120 sequentially calls two signature algorithms to calculate σ1=Sign_Dilithium(m) and σ2=Sign_Rainbow(m) respectively, and then uses an aggregation function.

[0084] (Equation 8)

[0085] Generate a fusion signature σ_final with a fixed length of 512 bits.

[0086] During verification, the verifier first obtains the two public keys of the principal from the aforementioned quantum blockchain distributed ledger network 300, and then sequentially verifies whether Verify_Dilithium(m, σ1) and Verify_Rainbow(m, σ2) are both true, and independently calculates... Then, it is compared with the received σ_final. Only if all three pass is the signature deemed valid.

[0087] Furthermore, the aforementioned post-quantum cryptography engine 120 supports flexible configuration of the threshold verification mode: in performance-priority scenarios (such as high-frequency IoT devices), the k value can be set to 1, meaning the verifier only needs to accept the signature using either of the two signature schemes, thus halving the signature length and reducing verification time by approximately 50%; while in high-security scenarios (such as financial transactions or government identity authentication), the k value can be set to 2, forcing both signature schemes to pass verification simultaneously. This implementation method requires attackers to simultaneously solve two different mathematical problems—the lattice problem and the multivariate problem—to forge a valid signature, and achieves a dynamic balance between security and computational performance through the threshold mode.

[0088] It is worth noting that the aforementioned Quantum Chain Distributed Ledger Network 300 adopts a quantum-resistant adaptive threshold consensus algorithm: based on the proof-of-stake framework, it replaces the block verification signature mechanism with a post-quantum threshold signature protocol.

[0089] Let the total number of verification nodes in the network be n, and the effective threshold value t be dynamically calculated according to the following formula: (Equation 4)

[0090] In the formula, α is the quantum security coefficient and α∈[0.6, 0.8]; a node quality assessment function is introduced.

[0091] Q(v)=w1·S(v)+w2·U(v)-w3·R(v) (Formula 5)

[0092] In the formula, S(v) is the normalized value of the number of tokens staked by the node, U(v) is the node's online time and stability score, and R(v) is the node's random number quality score. When Q(v) is lower than the preset threshold, the node is removed from the current consensus committee and replaced by a candidate node. The consensus process is not interrupted throughout the process.

[0093] In one embodiment of the present invention, the above-mentioned quantum chain distributed ledger network 300 is specifically implemented in the following manner.

[0094] First, the system operates based on the proof-of-stake framework, and replaces the block signature mechanism of all verification nodes (denoted as node set V, with a total of n) with a post-quantum threshold signature protocol, such as using a threshold variant based on CRYSTALS-Dilithium.

[0095] The system calculates the effective threshold value in real time.

[0096] (Equation 9)

[0097] In the formula, α is the quantum security coefficient and α∈[0.6, 0.8]. For example, when α=0.67, n=100 nodes, then t=67.

[0098] At the same time, before each round of consensus, the system calls the quality evaluation function.

[0099] Q(v)=w1·S(v)+w2·U(v)-w3·R(v) (Formula 5)

[0100] All nodes are scored, where S(v) is the normalized value of the number of staked tokens in the node (range 0 to 1), U(v) is the node's online time and stability score (increases by 0.01 every 24 hours of continuous online time, with a maximum of 1), and R(v) is the node's random number quality score (based on the entropy quality of the self-test report of the quantum true random number generator in the quantum-safe chip, range 0 to 1). The weight coefficients w1, w2, and w3 can be preset to 0.4, 0.4, and 0.2, respectively.

[0101] When the Q(v) of a node v is lower than a preset threshold (e.g., 0.6), the consensus protocol automatically triggers a committee reconfiguration process: the node is removed from the current consensus committee, and a node with the highest Q(v) is selected from the candidate node pool to replace it. At the same time, the shared key fragments are redistributed through the post-quantum threshold signature protocol. The entire process is designed with a pipeline to ensure that the consensus process is not interrupted, thus ensuring the Byzantine fault tolerance and continuous availability of the consensus protocol even in a quantum attack environment.

[0102] It is worth noting that the differential privacy noise addition in the aforementioned quantum privacy protection module 400 employs a distributed adaptive noise modulation algorithm.

[0103] For the query result f(D), first calculate the local sensitivity distribution Δf_local~Dist(μ, σ²). Define the noise generation function as a mixture of Laplace noise and Gaussian noise.

[0104] Introducing adaptive mixing coefficients

[0105] λ=Sigmoid(γ·(IQR(Δf_local)-τ)) (Formula 6)

[0106] In the formula, IQR is the interquartile range, τ is the preset dispersion threshold, and γ is the adjustment parameter. When the local sensitivity distribution exhibits long-tail characteristics, i.e., IQR > τ, λ → 1, switching to the Laplace-dominated mode; when the distribution is concentrated, λ → 0, switching to the Gaussian-dominated mode.

[0107] In one embodiment of the present invention, the quantum privacy protection module 400 receives a query request f(D) for a dataset D and calculates the local sensitivity distribution Δf_local~Dist(μ, σ²) of the query.

[0108] The specific method is as follows.

[0109] 1000 subsamples are randomly selected from the dataset, and the sensitivity value of each subsample is calculated. Then, the mean μ, variance σ², and interquartile range (IQR) of the distribution are fitted.

[0110] Next, the aforementioned quantum privacy protection module 400 obtains a preset dispersion threshold τ (e.g., τ=0.5) and an adjustment parameter γ (e.g., γ=5), and substitutes them into the adaptive mixing coefficient formula.

[0111] (Equation 10)

[0112] In the formula, the Sigmoid function compresses the output value to between 0 and 1.

[0113] Then, the aforementioned quantum privacy protection module 400 dynamically generates mixed noise based on the value of λ: if IQR > τ (indicating that the data exhibits a long-tailed distribution), then λ approaches 1, and the aforementioned quantum privacy protection module 400 primarily uses Laplace noise to generate noise ~ Lap(0, b), where b = Δf_global / ε, Δf_global is the global sensitivity, and ε is the privacy budget; if IQR ≤ τ (indicating that the data distribution is concentrated), then λ approaches 0, and the quantum privacy protection module 400 primarily uses Gaussian noise to generate noise ~ N(0, c²), where...

[0114] (Equation 11)

[0115] In the formula, δ is the allowed failure probability.

[0116] Finally, the aforementioned quantum privacy protection module 400 adds the generated noise to the query results and outputs the noisy result f'(D)=f(D)+Noise.

[0117] In practical deployments, when medical institutions query patient health data including extreme outliers (with high IQR), the aforementioned quantum privacy protection module 400 automatically switches to Laplace-dominated mode to protect the privacy of outlier patients. Conversely, when querying overall statistics with a uniform data distribution, the module automatically switches to Gaussian-dominated mode to improve query accuracy. Experiments show that this algorithm, under the same (ε,δ) privacy budget, can reduce the relative error of query results by 25% to 40% compared to a fixed noise mechanism, while preventing attackers from inferring the underlying data distribution by analyzing the statistical characteristics of the output noise.

[0118] It is worth noting that, in one embodiment of the present invention, the operating system 10 further includes a heterogeneous entity association and behavior anchoring algorithm. When registering a digital identifier for an automated entity, at least one responsible entity's digital identifier is forcibly associated. The key system of the automated entity adopts a hierarchical key derivation structure: the root key is issued by the responsible entity and stored in a quantum-safe chip, and the working key is derived from the root key through a key derivation function and used for daily signatures.

[0119] Three-factor binding signature is used when signing:

[0120] (Equation 7)

[0121] In the formula, T is the current timestamp; the system has a built-in lightweight behavior prediction model based on a temporal convolutional network. The input is a sequence of spatiotemporal feature vectors of historical signature behaviors, and the output is the expected behavior hash at the next moment. When the semantic distance between the actual signature and the predicted hash exceeds a dynamic threshold, a sequence of actions is triggered, including rejecting the signature, alerting the responsible entity, and optionally automatically freezing the digital identifier of the automated entity.

[0122] For example, when registering a digital identifier for an automated entity (such as a delivery robot), the administrator forcibly selects a registered responsible entity's digital identifier (such as the enterprise entity "E@SF Express.bit") as the associated object through a terminal, and records this binding relationship on the aforementioned quantum blockchain distributed ledger network 300, forming an immutable legal responsibility link. Subsequently, the aforementioned quantum-safe chip 100 generates a hierarchical key system for the automated entity: the root key SK_root is signed by the responsible entity using its subsequent quantum private key and injected into the protected storage area of ​​the aforementioned quantum-safe chip 100, while the working key SK_work is automatically derived daily through the key derivation function KDF(SK_root, salt, "delivery"), used for daily signature operations to reduce the risk of root key exposure.

[0123] Each time a signature is made, the automated entity performs a three-factor binding signature.

[0124] (Equation 7)

[0125] In the formula, T is the current timestamp, which makes the signature simultaneously include real-time authorization of the working key, long-term endorsement of the responsible entity, and freshness in the time dimension.

[0126] Meanwhile, the system deploys a lightweight behavior prediction model based on a temporal convolutional network (TCN) in the cloud. This model takes the spatiotemporal feature vector sequence of the past 30 signatures of the automated subject (including signature timestamps, geolocation hashes, instruction type encodings, signature frequencies, etc.) as input and outputs the expected behavior hash value at the next moment.

[0127] Before each signature, the aforementioned quantum-safe chip 100 compares the current signature content with the expected behavior hash returned by the TCN model, calculating the semantic distance between the two in the twin network embedding space. If this distance exceeds a dynamic threshold (which is automatically adjusted based on the statistical distribution of historical behavior deviations, for example, set to three times the standard deviation of the mean), the following sequence of actions is triggered: first, the signature request is rejected and an error code is returned; then, an abnormal behavior alarm (including detailed information about the abnormal signature) is sent to the responsible entity through the aforementioned quantum blockchain distributed ledger network 300; finally, the digital identifier of the automated entity is optionally and automatically frozen for 24 hours according to a preset strategy, during which time all signature requests will be directly rejected. This implementation makes every action of the automated entity traceable to the bound responsible entity, and at the same time, it achieves proactive defense against abnormal or malicious behavior through real-time behavior prediction.

[0128] Please refer to Figure 2 . Figure 2 This is a flowchart of a digital identity authentication method based on quantum blockchain according to one embodiment of the present invention. Figure 2 As shown, the above-mentioned digital identity authentication method includes the following steps: S1. The user inputs a digital identifier through a terminal, and the quantum security chip 100 generates a public-private key pair, binding and recording the digital identifier, public key, message digest, and network address prefix in the aforementioned quantum chain distributed ledger network. S2. The quantum security chip 100 derives a network layer address based on the digital identifier, which serves as the network identity identifier of the subject. S3. The verifier inputs the digital identifier, obtains the public key and network address prefix through the aforementioned quantum chain distributed ledger network, and verifies the signature or initiates communication. S4. When data analysis or decision-making is required, a privacy protection process is triggered. S5. Offline mode is supported, completing digital identifier verification and address derivation through locally cached data.

[0129] It is worth noting that in step S2 above, the address derivation process employs an entropy source hybrid and key derivation linkage algorithm: each time a derivation occurs, a first random number is extracted from a true random number source, and a second random number is extracted from the physical non-cloning function of the aforementioned quantum security chip 100; the first random number, the second random number, the current derivation counter, and the hash value of the digital identifier are input into the key derivation function to generate a derivation key; the derivation key is divided into the interface identifier of the network address, the temporary key for the current session, and the pre-key for the next derivation; each derivation consumes the pre-key and the derivation counter monotonically increases, ensuring that the derivation sequence satisfies forward security and backward security; this algorithm ensures that even if the current session key is leaked, it is impossible to deduce the historical or future network address and session key.

[0130] In one embodiment of the present invention, the quantum-safe chip 100 obtains input from three independent entropy sources each time it derives: it extracts a 128-bit first random number R1 from an integrated true random number source (e.g., a quantum true random number generator (QRNG)); it extracts a 128-bit second random number R2 from a physically unclonable function (PUF) inside the quantum-safe chip 100 (the PUF response is based on physical differences that cannot be replicated during chip manufacturing, and has unique and stable characteristics); and it reads the current derivation counter C from the security register of the quantum-safe chip 100 (the counter is initially 0 and automatically increments by 1 after each derivation).

[0131] Then, the aforementioned quantum-safe chip 100 calculates the hash value of the digital identifier.

[0132] HID=SHAKE256(the normalized string of quantum digital identifier 200) (Equation 12)

[0133] Then, HID, R1, R2, and C are concatenated and input into the key derivation function KDF, specifically,

[0134] (Equation 12)

[0135] Output a 512-bit derived key DK.

[0136] Next, the address derivation unit 130 divides DK into three parts: the lower 128 bits are the interface identifier A_addr=DK[0:127] for the network address, the middle 256 bits are the temporary key K_session=DK[128:383] for this session, and the upper 128 bits are the pre-key K_next=DK[384:511] for the next derivation.

[0137] The aforementioned quantum-safe chip 100 binds K_next to the counter C+1 and stores it in a secure register for use in the next derivation. When the derivation counter C increments to C+1, the input for the next derivation will include the new pre-key K_next (as the output of the previous derivation), a new PUF response, and a random number, forming a hash chain structure.

[0138] This algorithm ensures that even if an attacker obtains the temporary key K_session for the current session, they cannot deduce future network addresses and session keys due to the lack of the pre-key K_next for the next derivation and the new entropy source inputs R1 and R2. Similarly, since each derivation consumes a pre-key and the derivation counter monotonically increases, even if an attacker obtains the current address A_addr, they cannot deduce historical addresses in reverse, thus simultaneously satisfying forward and backward security.

[0139] It is worth noting that the privacy protection process in step S4 above adopts a fine-grained dynamic privacy budget allocation algorithm: each subject sets a privacy preference vector and a corresponding privacy budget allocation ratio during registration; the system maintains a total privacy budget counter; for queries involving attribute categories, the actual privacy budget consumed is calculated based on the base budget, preference coefficient, and allocation ratio; a privacy budget reuse mechanism is introduced, so that for similar queries by the same subject within a time window, only one privacy budget is charged; a privacy budget lending mechanism is introduced: subjects are allowed to temporarily overdraw their budget, and the overdrawn portion is repaid at double the interest rate in the next cycle; when the remaining budget is insufficient and there is no lending quota, the query is rejected and an optional data fuzzification alternative is returned.

[0140] In one embodiment of the present invention, each subject sets a privacy preference vector Φ=(φ1, φ2, …, φm) and a corresponding privacy budget allocation ratio Ω=(ω1, ω2, …, ωm) via a terminal interface during registration. Here, φi represents the sensitivity to the i-th type of sensitive attribute (such as location, health, or finance) (range 0 to 1), and ωi represents the privacy budget ratio allocated to that type of attribute (satisfying Σωi=1). These parameters are signed by the aforementioned quantum-safe chip 100 and stored on the aforementioned quantum blockchain distributed ledger network 300.

[0141] The aforementioned quantum privacy protection module 400 also maintains a total privacy budget counter ε_remaining for each subject, with an initial value of the total authorized budget ε_total for that subject (e.g., ε_total = 10.0). When a query involving attribute category i is received, the aforementioned quantum privacy protection module 400 first calculates the privacy budget that should be consumed for this query.

[0142] (Equation 13)

[0143] In the formula, ε_base is the base single query budget (e.g., ε_base=0.1), and η is the adjustment coefficient (e.g., η=0.5).

[0144] The aforementioned quantum privacy protection module 400 then executes a privacy budget reuse mechanism: calculating the semantic similarity between the current query and historical queries (using the Sentence-BERT model to encode the query statement into a vector and then calculating the cosine similarity). If the similarity with any query within a past time window W (e.g., 1 hour) exceeds 0.85, it is considered a duplicate query, and only 10% of the original budget, i.e., 0.1·ε_consumed, is charged. If the remaining budget ε_remaining is insufficient and there is no available loan amount, the aforementioned quantum privacy protection module 400 initiates a loan mechanism, allowing the entity to temporarily overdraw, with an overdraw limit of ε_total·0.2, but the overdrawn portion must be repaid in double the amount in the next settlement cycle. Repayment is made at double the interest rate (i.e., deducting twice the overdraft amount); when ε_remaining < ε_consumed and there is no loan limit, the aforementioned quantum privacy protection module 400 rejects the query and automatically returns a data obfuscation alternative (such as replacing the detailed data with a prompt message "This data is protected by privacy and can only be viewed as a statistical summary", or returning a summed statistical value instead of a detailed list); after each query is processed, the aforementioned quantum privacy protection module 400 updates ε_remaining = ε_remaining - ε_consumed (or subtracts the discounted value if a reuse mechanism is used), and stores the query record in the historical cache for subsequent reuse detection.

[0145] This implementation results in queries for highly sensitive attributes (such as health information) consuming more budget and queries for less sensitive attributes (such as device model) consuming less budget. At the same time, through reuse and borrowing mechanisms, the number of effective queries can be increased by more than 60% under the same total budget.

[0146] It is worth noting that, in one embodiment of the present invention, the above-mentioned digital identity authentication method further includes a lossless hot migration algorithm for a cryptographic algorithm: the cryptographic update engine maintains a multi-version algorithm container, which supports running at least three versions of the cryptographic algorithm simultaneously.

[0147] The algorithm upgrade process includes: a preloading phase, where the algorithm upgrade package, authenticated by multi-signature, is received and its integrity and correctness are verified in an isolated execution environment; a shadow mode phase, where the new algorithm and the current algorithm run simultaneously to generate dual signatures, but only the current algorithm is used for verification, while the new algorithm is only used for correctness monitoring; a shadow verification phase, where a preset time window is monitored, and if the dual signature consistency rate exceeds a preset threshold, the process proceeds to the next phase; an atomic switching phase, where the new algorithm is promoted to the current algorithm under the witness of the consensus network, and the original current algorithm is downgraded to the legacy algorithm; a compatibility period phase, where the legacy algorithm is retained for a preset number of days to handle delayed or offline transactions; and a cleanup phase, where the legacy algorithm slots are released after the expiration period.

[0148] Throughout the migration process, different nodes in the network may be at different migration stages, and the highest version algorithm supported by both parties can be automatically selected for communication through a version negotiation protocol.

[0149] In one embodiment of the present invention, the post-quantum cryptography engine 120 maintains a multi-version algorithm container that supports the simultaneous operation of at least three versions of cryptographic algorithm slots, namely the currently active slot Alg_current, the next version slot Alg_next, and the legacy compatibility slot Alg_legacy.

[0150] When the system administrator receives a multi-signature-authenticated algorithm upgrade package (e.g., from CRYSTALS-Dilithium to FALCON+, a Fast-Fourier Lattice-based Compact Signatures over NTRU, via the Quantum Chain distributed ledger network 300), the migration process enters the pre-loading phase: the aforementioned post-quantum cryptography engine 120 loads the new algorithm code into the Alg_next slot and performs a correctness self-check using 1000 sets of pre-built test vectors in an isolated execution environment to ensure that the signing and verification functions of the new algorithm are completely correct.

[0151] After passing the self-test, the system enters the shadow mode stage: The above-mentioned post-quantum cryptography engine 120 is configured to run Alg_current and Alg_next simultaneously. For each message m to be signed, the two slots generate signatures σ_current and σ_next respectively. However, the verifier only uses σ_current for normal transaction verification, and σ_next is only recorded in the local log for correctness monitoring.

[0152] The shadow mode runs continuously for a preset time window (e.g., 24 hours). During this period, the post-quantum cryptography engine 120 continuously calculates the double signature consistency rate. If the consistency rate reaches a preset threshold (e.g., above 99.99%) and no abnormal alarm is detected, the atomic switching phase begins. The post-quantum cryptography engine 120 broadcasts the algorithm switching proposal to the entire network through the quantum chain distributed ledger network 300. After waiting for a consensus cycle (approximately 2 seconds), the pointers of Alg_current and Alg_next are atomically exchanged under the witness of the consensus network, making the new algorithm immediately effective as the current algorithm, and the original current algorithm downgraded to Alg_legacy.

[0153] Then, the compatibility phase begins: the Alg_legacy slot is reserved for a preset number of days (e.g., 7 days) to verify messages signed by delayed transactions or offline devices using old algorithms that may exist in the network. When processing such messages, the aforementioned post-quantum cryptography engine 120 automatically identifies the signature version and calls the corresponding slot for verification.

[0154] After the compatibility period ends, the cleanup phase begins: the aforementioned post-quantum cryptography engine 120 releases the Alg_legacy slot resources, making them available for the next upgrade.

[0155] Throughout the migration process, different nodes in the network may be at different migration stages (for example, some nodes have completed atomic switching while others are still in shadow mode). The aforementioned post-quantum cryptography engine 120 automatically handles this through a version negotiation protocol: when two nodes communicate, they exchange lists of the algorithm versions they support. The protocol automatically selects the highest version algorithm that both parties support for signing and verification, ensuring compatibility across versions. This achieves zero downtime, zero data loss, and hot upgrades for cryptographic algorithms with zero compatibility issues, maintaining system availability above 99.999%.

[0156] For example, user Zhang San registers and uses identity verification.

[0157] Step S1: User Zhang San inputs the quantum digital identifier 200 as "P@ZhangSan.cn" through the terminal. The quantum security chip 100 calls the post-quantum cryptography engine 120 to generate heterogeneous post-quantum key pairs (e.g., CRYSTALS-Dilithium lattice base key pair and Rainbow multivariate key pair). Subsequently, the quantum security chip 100 binds and records the quantum digital identifier 200, the post-quantum public key hash value, the subject information digest (e.g., ID card hash) and the network address prefix (e.g., 2001:db8:1:: / 48) in the quantum chain distributed ledger network 300 through the quantum chain client, forming an immutable on-chain mapping entry.

[0158] Step S2: The address derivation unit 130 of the quantum security chip 100 calls the dynamic verifiable obfuscated address derivation algorithm based on the quantum digital identifier 200 and the subsequent quantum public key registered in step S1. Taking the current time parameter T_t (e.g., activating day 3) and the previous cycle address A_t-1 as input, it calculates the IPv6 network layer address A_t=2001:db8:1:2:7c3a:2b4f:9d6e:1a8b for the current cycle, which serves as Zhang San's network identity identifier for that time cycle.

[0159] Step S3: After receiving the transaction request initiated by Zhang San, the verifying enterprise B inputs Zhang San's quantum digital identifier 200 "P@ZhangSan.cn" into the aforementioned quantum blockchain distributed ledger network 300. The quantum blockchain distributed ledger network returns Zhang San's post-quantum public key and network address prefix. Enterprise B uses the returned public key to verify the fused signature attached to the transaction. After successful verification, Zhang San's identity is confirmed, and encrypted communication is directly initiated using the derived IPv6 address 2001:db8:1:2:7c3a:2b4f:9d6e:1a8b.

[0160] Step S4: When Enterprise B's AI system needs to analyze Zhang San's health data, the quantum privacy protection module 400 is triggered. This module calls the aforementioned distribution adaptive noise modulation algorithm to apply adaptive mixed noise to the query results (dynamically adjusting the ratio of Laplace and Gaussian noise according to the data distribution characteristics). At the same time, it calls the aforementioned fine-grained privacy budget dynamic allocation algorithm to deduct the consumption of this query (e.g., ε_consumed=0.6) from Zhang San's preset total privacy budget, ensuring that the output results meet the differential privacy protection requirements.

[0161] Step S5: When Zhang San is in a network-free environment (such as an underground parking lot), the quantum security chip 100 of his terminal device reads the on-chain data cached locally (including its own digital identifier mapping record and the public key of the verifier). The quantum security chip 100 directly executes the address derivation algorithm and signature verification logic of step S2 to complete offline identity authentication. After the network is restored, the offline transaction records are batch synchronized to the quantum chain distributed ledger network 300.

[0162] The core advantage of this invention lies in the deep integration of the quantum-safe chip 100, the quantum chain distributed ledger network 300, and the quantum privacy protection module 400. For the first time, a unified architecture where "a single quantum digital identifier 200 simultaneously represents both legal identity and network location" is achieved at the operating system level. Users only need to remember a human-readable identifier (such as "P@Zhangsan.cn"), and the system can dynamically derive an unlinkable IPv6 address and perform quantum-safe identity authentication. This completely solves the fundamental defects of traditional solutions, such as the separation of identity and address and the leakage of privacy due to address traceability. At the same time, by integrating signature algorithms and lossless hot migration algorithms through a heterogeneous cryptographic system, this invention can maintain overall security even when a single algorithm is quantum-breakable and supports zero-downtime upgrades. Thus, in an era where the threat of quantum computing is increasingly looming, this invention provides the digital society with a unique ultimate identity infrastructure that integrates quantum-resistant security, address privacy protection, unified human-machine management, and cryptographic agility.

[0163] The embodiments of the present invention described above can be implemented in various hardware, software codes, or combinations thereof. For example, embodiments of the present invention can also be program code executing the above methods in a Digital Signal Processor (DSP). The present invention can also relate to various functions executed by a computer processor, digital signal processor, microprocessor, or Field Programmable Gate Array (FPGA). The processor described above can be configured to perform specific tasks according to the present invention, which are accomplished by executing machine-readable software code or firmware code defining the specific methods disclosed in the present invention. The software code or firmware code can be developed into different programming languages ​​and different formats or forms. The software code can also be compiled for different target platforms. However, the different code styles, types, and languages ​​of the software code performing tasks according to the present invention and other types of configuration code do not depart from the spirit and scope of the present invention.

[0164] Therefore, those skilled in the art will recognize that although embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Therefore, the scope of the present invention should be understood and recognized as covering all such other variations or modifications.

Claims

1. A digital identity management operating system based on quantum blockchain, comprising a quantum secure chip and a quantum blockchain distributed ledger network; The quantum chain distributed ledger network is used to record the mapping relationship between quantum digital identifiers and the subject's post-quantum public key, digital identity identifier, subject information digest, and network layer address prefix, and provides decentralized resolution services; The quantum-safe chip includes: A multi-source authentication data storage partition is used to store the digest of subject information certified by at least one certification authority; A post-quantum cryptography engine is used to generate and store post-quantum public-private key pairs to perform post-quantum signatures and verifications. An address derivation unit is used to generate network layer addresses based on quantum digital identifiers and post-quantum public keys.

2. The digital identity management operating system according to claim 1, characterized in that, The address derivation unit uses a dynamically verifiable obfuscated address derivation algorithm to define the address derivation function: F(S, K, N, T)→A In the formula, S is the normalized representation of the digital identifier, K is the hash value of the public key, N is the unique serial number of the chip, and T is the time parameter; The address derivation function is specifically... In the formula, H is the quantum-resistant hash function, and ⊕ is the XOR operation; The derived address satisfies the condition that, given (S,K,N), the validity of any historical address A_t can be verified, but A_{t-1} cannot be deduced from the current address A_t or A_{t+1} can not be predicted.

3. The digital identity management operating system according to claim 1, characterized in that, The post-quantum cryptography engine executes a heterogeneous cryptosystem fusion signature algorithm: At the same time, maintain at least two signature schemes Σ1 and Σ2 based on different signature schemes, where Σ1 is based on the lattice problem and Σ2 is based on the encoding problem or the multivariate problem; When generating the signature, σ1=Sign_Σ1(m) and σ2=Sign_Σ2(m) are calculated for message m respectively; Using aggregate functions Generate the fusion signature σ_final; During verification, the following conditions must be met simultaneously: Verify_Σ1(m, σ1)=True, Verify_Σ2(m, σ2)=True, and σ_final must be consistent with the aggregation result. The fusion signature supports a threshold verification mode, which is configured to pass verification by passing any k schemes (k≥1).

4. The digital identity management operating system according to claim 1, characterized in that, The quantum blockchain distributed ledger network employs a quantum-resistant adaptive threshold consensus algorithm. Based on the proof-of-stake framework, the signature mechanism for block verification is replaced with a post-quantum threshold signature protocol; Let the total number of verification nodes in the network be n, and the effective threshold value t be dynamically calculated according to the following formula. In the formula, α is the quantum security coefficient and α∈[0.6, 0.8]; Introducing a node quality evaluation function Q(v)=w1·S(v)+w2·U(v)-w3·R(v) In the formula, S(v) is the normalized value of the number of tokens staked by the node, U(v) is the node's online time and stability score, and R(v) is the node's random number quality score. When Q(v) falls below a preset threshold, the node is removed from the current consensus committee and replaced by a candidate node. The consensus process is not interrupted throughout the process.

5. The digital identity management operating system according to claim 1, characterized in that, It also includes a quantum privacy protection module for integrating at least one privacy enhancement technique, wherein the differential privacy noise addition in the quantum privacy protection module employs a distributed adaptive noise modulation algorithm: For the query result f(D), first calculate the local sensitivity distribution Δf_local~Dist(μ, σ²); The noise generation function is defined as a mixture of Laplace noise and Gaussian noise; Introducing adaptive mixing coefficients λ=Sigmoid(γ·(IQR(Δf_local)-τ)) In the formula, IQR is the interquartile range, τ is the preset dispersion threshold, and γ is the adjustment parameter; When the local sensitivity distribution exhibits long-tail characteristics, i.e., IQR>τ, λ→1, switching to the Laplace-dominated mode; When the distribution is concentrated, λ→0, switching to the Gaussian-dominated mode.

6. The digital identity management operating system according to any one of claims 1 to 5, characterized in that, It also includes a heterogeneous subject association and behavior anchoring algorithm: When registering a digital identifier for an automated entity, it is mandatory to associate it with at least one responsible entity's digital identifier; The key system of the automated entity adopts a hierarchical key derivation structure. The root key is issued by the responsible entity and stored in a quantum-safe chip. The working key is derived from the root key through a key derivation function and used for daily signatures. Three-factor binding signature is used for signing. In the formula, T is the current timestamp; The system has a built-in lightweight behavior prediction model based on a temporal convolutional network. The input is a sequence of spatiotemporal feature vectors of historical signature behaviors, and the output is the hash of the expected behavior at the next time step. When the semantic distance between the actual signature and the predicted hash exceeds a dynamic threshold, a sequence of actions is triggered, including rejecting the signature, alerting the responsible entity, and optionally automatically freezing the digital identifier of that entity.

7. A digital identity authentication method based on the digital identity management operating system according to any one of claims 1 to 6, comprising the following steps: S1. The user inputs a digital identifier through the terminal, and the quantum security chip generates a public-private key pair, and binds and records the digital identifier, public key, message digest and network address prefix in the quantum chain distributed ledger network. S2. The quantum-safe chip derives a network layer address from a digital identifier, which serves as the network identity identifier for the main entity. S3. The verifier inputs a digital identifier, obtains the public key and network address prefix through the quantum chain distributed ledger network, and verifies the signature or initiates communication. S4. Trigger the privacy protection process when data analysis or decision-making is required; S5 supports offline mode, and completes digital identifier verification and address derivation through local cached data.

8. The digital identity authentication method according to claim 7, characterized in that, The address derivation process in step S2 employs an entropy source mixing and key derivation linkage algorithm: Each time a random number is derived, a first random number is extracted from a true random number source, and a second random number is extracted from the physical no-cloning function of the quantum-safe chip. Input the first random number, the second random number, the current derivation counter, and the hash value of the numeric identifier into the key derivation function to generate the derived key; The derived key is divided into the interface identifier of the network address, the temporary key for this session, and the pre-key for the next derivation. Each derivation consumes a prekey and the derivation counter monotonically increases.

9. The digital identity authentication method according to claim 7, characterized in that, The privacy protection process in step S4 employs a fine-grained dynamic privacy budget allocation algorithm: Each entity sets a privacy preference vector and a corresponding privacy budget allocation ratio during registration; The system maintains a total privacy budget counter; For queries involving attribute categories, the actual privacy budget consumed is calculated based on the base budget, preference coefficient, and allocation ratio. A privacy budget reuse mechanism is introduced, so that for similar queries by the same subject within a time window, only one privacy budget is charged; A privacy budget lending mechanism is introduced, allowing entities to temporarily overdraw their budgets, with the overdrawn portion to be repaid at double the interest rate in the next cycle; When the remaining budget is insufficient and there is no available loan amount, the query is rejected and an optional data obfuscation alternative is returned.

10. The digital identity authentication method according to any one of claims 7 to 9, characterized in that, It also includes a lossless hot migration algorithm for cryptographic algorithms, and the cryptographic update engine maintains a multi-version algorithm container that supports running at least three versions of cryptographic algorithms simultaneously. The algorithm upgrade process includes: During the preloading phase, the algorithm upgrade package, which has been authenticated by multiple signatures, is received, and the integrity and correctness of the algorithm are verified in an isolated execution environment. In the shadow mode phase, the new algorithm and the current algorithm run simultaneously to generate dual signatures, but only the current algorithm is used for verification, while the new algorithm is only used for correctness monitoring. During the shadow verification phase, a preset time window is monitored. If the dual signature consistency rate exceeds a preset threshold, the process proceeds to the next phase. During the atomic switching phase, the new algorithm is promoted to the current algorithm under the witness of the consensus network, and the original current algorithm is downgraded to the legacy algorithm. During the compatibility period, the legacy algorithm will be reserved for a preset number of days to handle delayed or offline transactions; During the cleanup phase, legacy algorithm slots will be released upon expiration. Throughout the migration process, different nodes in the network may be at different migration stages, and the highest version algorithm supported by both parties can be automatically selected for communication through a version negotiation protocol.

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