Key management optimization method based on post-quantum cryptographic algorithm

Abstract

The application relates to the technical field of information security, and discloses a key management optimization method based on a post-quantum cryptographic algorithm. The method first obtains a noise-resistant post-quantum key by using a lattice-based key generation algorithm and a fault-tolerant encoding technology; then generates a multivariate encryption key and a layered verification key through a multivariate polynomial encryption algorithm and a hash chain structure; then realizes key fragment storage and a dynamic threshold signature by using a distributed hash tree technology and a threshold signature protocol; then adjusts the weight of the key fragments and verifies the key fragments by using a dynamic weight updating algorithm and a zero-knowledge proof protocol; and finally completes key anonymous revocation and safe destruction by using a revocable ring signature algorithm and a quantum secure erasure protocol. The application effectively improves the security and reliability of key management, can cope with the challenge brought by quantum computing, and has important application value in the field of information security.

Description

Technical Field

[0001] This invention relates to the field of information security technology, specifically to a key management optimization method based on post-quantum cryptography algorithms. Background Technology

[0002] In today's digital age, information security is crucial for protecting individual privacy, corporate interests, and national sovereignty. As the core of encrypting and decrypting data, the security and effectiveness of key management are paramount. Traditional cryptographic algorithms have played a vital role in long-term applications, but with the rapid development of quantum computing technology, these algorithms are facing unprecedented challenges.

[0003] The immense computing power of quantum computers theoretically enables the rapid cracking of mathematical problems upon which traditional cryptographic algorithms rely (such as the elliptic curve discrete logarithm problem and the shortest vector problem in lattice theory). For example, elliptic curve cryptography relies on the difficulty of the elliptic curve discrete logarithm problem to ensure security; however, quantum computers can use Scholl's algorithm to solve such mathematical problems in polynomial time, rendering elliptic curve cryptography insecure in a quantum computing environment. Similarly, the Diffie-Hellman key exchange protocol, based on the elliptic curve discrete logarithm problem, faces the same predicament. Once quantum computers are widely deployed, the security of many existing encrypted communication, financial transaction, and data storage systems will be severely threatened.

[0004] Traditional methods for key management also have many problems. On the one hand, during key generation, it is difficult to ensure that the generated keys have sufficient randomness and security, making them vulnerable to analysis and cracking by attackers. For example, some key generation methods based on pseudo-random number generators may generate key sequences with certain regularities. Attackers, by studying the generation algorithm and obtaining partial keys, may be able to predict subsequent keys. On the other hand, there are risks in key storage and distribution. In centralized key storage, once attacked, all keys may be leaked; while in distributed storage, ensuring the security of key fragments and the accurate and rapid acquisition and combination of key fragments when needed is a challenge. Furthermore, traditional methods are often inefficient and insecure in terms of key updates and revocations. For example, key updates may require significant computational and communication overhead to regenerate and distribute keys; and in key revocation, it is difficult to ensure that revoked keys will not be reused.

[0005] Post-quantum cryptography offers a new direction for solving the aforementioned problems. It is based on mathematical problems considered secure even in quantum computing environments, such as lattice theory, solving multivariable polynomial equations, and coding-based cryptography. However, the application of post-quantum cryptography in key management is still in the exploratory stage, with many areas requiring optimization and improvement. For example, how to design efficient key generation methods using post-quantum cryptography to improve key security and generation efficiency; how to utilize post-quantum cryptography to implement more secure and reliable key storage and distribution mechanisms; and how to optimize key update and revocation processes to adapt to the characteristics of post-quantum cryptography. Therefore, researching an optimized key management method based on post-quantum cryptography is of significant practical importance and urgency. Summary of the Invention

[0006] The purpose of this invention is to provide a key management optimization method based on post-quantum cryptography algorithms to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a key management optimization method based on post-quantum cryptography, the method comprising: Step S1: The initial security parameters are constructed using a lattice-based key generation algorithm to obtain the post-quantum key generation basis; and the post-quantum key generation basis is then processed using fault-tolerant coding techniques to obtain a noise-resistant post-quantum key. Step S2: Perform dynamic polynomial mapping processing on the noise-resistant quantum key using a multivariate polynomial encryption algorithm to obtain a multivariate encryption key; perform layered binding processing on the multivariate encryption key through a hash chain structure to obtain a layered verification key; Step S3: Use distributed hash tree technology to perform fragmented storage processing on the hierarchical verification key to obtain distributed key fragments; and perform dynamic threshold signature processing on the distributed key fragments based on the threshold signature protocol to obtain threshold signature key fragments. Step S4: Periodically adjust the weights of the threshold signature key fragments using a dynamic weight update algorithm to obtain updated weight key fragments; perform non-interactive verification on the updated weight key fragments using a zero-knowledge proof protocol to obtain verified key fragments. Step S5: Anonymously revoke the verified key fragments using the revocable ring signature algorithm to obtain the revocation identifier key; and then use a secure erasure protocol to quantum-safely destroy the revocation identifier key to obtain the final key management result.

[0008] Preferably, step S1 includes the following steps: Step S11: Use a lattice basis generating function to construct a lattice basis for the initial security parameters, wherein the initial security parameters include the modulus, dimension, and error distribution; Step S12: Based on the lattice basis output by the lattice basis generation function, the lattice basis is subjected to fault-tolerant coding processing using fault-tolerant coding technology to obtain a noise-resistant quantum key; Step S13: Extract the basic key components from the noise-resistant quantum key using a random sampling algorithm to obtain the basic key set; Step S14: Perform linear superposition processing on the basic key set using a linear combination algorithm to generate the final noise-resistant quantum key.

[0009] Preferably, step S2 includes the following steps: Step S21: Construct a system of multivariable polynomial equations, where the degree of each polynomial is and the number of variables is , and generate the polynomial coefficient matrix using a random coefficient generation algorithm; Step S22: Map the noise-resistant quantum key to the input variables of the multivariable polynomial equation system, and obtain the multivariable encryption key by solving the equation system; Step S23: Use a hash chain structure to perform layer-by-layer hash binding on the multivariate encryption key to generate a layered verification key; Step S24: Perform chained signature processing on the hierarchical verification key using the verification chain generation algorithm to obtain a verifiable key hash chain.

[0010] Preferably, the generation function for the hash chain structure in step S23 is as follows: in, Let i be the hash value of the i-th layer. For the multivariate encryption key components of the i-th layer, H represents the XOR operation, and H is the collision-resistant hash function.

[0011] Preferably, step S3 includes the following steps: Step S31: Use distributed hash tree technology to divide the hierarchical verification key into m key fragments, where m≥2; Step S32: Define a minimum signature threshold t based on the threshold signature protocol, requiring at least t key fragments to jointly generate a valid signature; Step S33: Use the Lagrange interpolation algorithm to perform polynomial reconstruction processing on the m key fragments to obtain the threshold signature key fragments; Step S34: Perform independent validity verification on each threshold signature key fragment using the fragment verification function.

[0012] Preferably, the formula for the fragmentation verification function in step S34 is as follows: in, The verification value for the j-th fragment. For the signature component of the i-th slice, Let p be the value of the Lagrange polynomial at 0, and p be a large prime number.

[0013] Preferably, step S4 includes the following steps: Step S41: Construct a dynamic weight update function to calculate the weight value of each key fragment based on historical usage frequency and fragment trust level; Step S42: Normalize the weight values ​​using a weighted average algorithm to obtain an updated weight allocation scheme; Step S43: Generate verification proofs for each key fragment based on a non-interactive zero-knowledge proof protocol; Step S44: Aggregate all verification proofs into a global verification result using a proof aggregation algorithm, and generate a post-verification key fragment.

[0014] Preferably, the formula for the dynamic weight update function in step S41 is as follows: in, Let i be the weight of the i-th slice. Historical usage frequency Rate trust level and This is the dynamic adjustment coefficient.

[0015] Preferably, step S5 includes the following steps: Step S51: Generate a ring signature containing a revocable tag using the revocable ring signature algorithm, where the number of ring members is n; Step S52: Identify the key fragment to be destroyed using the revocation tag via an anonymous revocation function; Step S53: The identifier fragment is overwritten and randomized multiple times based on the quantum-safe erasure protocol to ensure that the information is unrecoverable; Step S54: Use the erase verification function to perform entropy detection on the destroyed storage area to confirm the integrity of the destruction.

[0016] Preferably, the execution steps of the quantum-safe erasure protocol in step S53 include: Step S531: Perform at least three full-disk random data overwrites on the key storage medium; Step S532: Use a quantum random number generator to generate a true random number sequence and replace the original stored content; Step S533: Verify whether the medium meets the preset entropy threshold using a physical damage detection algorithm.

[0017] Compared with the prior art, the beneficial effects of the present invention are: This invention is based on a post-quantum cryptography algorithm, utilizing a lattice-based key generation algorithm and fault-tolerant coding techniques to generate a noise-resistant post-quantum key from initial security parameters. The lattice problem upon which the lattice-based algorithm relies possesses high security in a quantum computing environment, making it difficult for quantum computers to crack. The fault-tolerant coding technique further enhances the key's resistance to noise and errors, ensuring key integrity and availability in complex communication and storage environments. In the presence of noise interference in quantum channels, traditional keys may malfunction, leading to incorrect data decryption. However, the noise-resistant post-quantum key generated by this invention effectively resists noise effects, guaranteeing secure data transmission and storage.

[0018] By employing a multivariate polynomial encryption algorithm to perform dynamic polynomial mapping on the key, combined with a hash chain structure and a verification chain generation algorithm, the generation and verification of multivariate encryption keys and hierarchical verification keys are realized. The complexity of the multivariate polynomial encryption algorithm enhances the security of the encrypted key, while the hash chain structure and verification chain provide a reliable method for key verification. During data transmission, the receiver can quickly and accurately verify the authenticity and integrity of the key through the verification chain, preventing key tampering or forgery.

[0019] By utilizing distributed hash tree technology and a threshold signature protocol, hierarchical verification keys are fragmented for storage and dynamically thresholded for signature processing. Distributed hash tree technology stores key fragments across different nodes, reducing the risk of centralized key storage; the threshold signature protocol stipulates that a valid signature can only be generated when a certain number of key fragments are combined, thus improving key signature security. In the distributed storage system, even if key fragments on some nodes are stolen, attackers cannot generate valid signatures, ensuring system security.

[0020] The dynamic weight update algorithm periodically adjusts the weights of threshold signature key fragments based on historical usage frequency and fragment trust levels, enabling zero-knowledge proof protocols to achieve interactive verification. This dynamic management approach optimizes the weight allocation of key fragments based on actual key usage and node trust levels, improving the efficiency and security of key usage. In a network environment where node trust levels dynamically change, the dynamic weight update algorithm can adjust the weights of key fragments in a timely manner, ensuring that key fragments from high-trust nodes play a greater role in key usage.

[0021] The revocable ring signature algorithm enables anonymous revocation, while the quantum-safe erasure protocol ensures the secure destruction of the revocation identifier key. Anonymous revocation protects user privacy, and the quantum-safe erasure protocol, through multiple overwrites and randomization processes, guarantees that the key information is unrecoverable. When a user needs to revoke a key, the revocable ring signature algorithm can complete the revocation operation without revealing the user's identity; the quantum-safe erasure protocol prevents the residual data of the revoked key from being recovered and reused by attackers, further improving the security of key management. Attached Figure Description

[0022] Figure 1 This is a schematic diagram illustrating the working principle of the key management optimization method described in this invention. Figure 2 A flowchart illustrating the key generation and processing workflow; Figure 3 A flowchart illustrating the workflow for key fragment storage and signature verification; Figure 4 A flowchart of the key weight adjustment process. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Please see Figure 1-4 This invention provides a key management optimization method based on post-quantum cryptography algorithms, the overall implementation of which is as follows: Step S1: The initial security parameters are constructed using a lattice-based key generation algorithm to obtain the post-quantum key generation basis; and the post-quantum key generation basis is processed using fault-tolerant coding technology to obtain a noise-resistant post-quantum key.

[0025] Step S2: Perform dynamic polynomial mapping processing on the noise-resistant quantum key using a multivariate polynomial encryption algorithm to obtain a multivariate encryption key; perform hierarchical binding processing on the multivariate encryption key through a hash chain structure to obtain a hierarchical verification key.

[0026] Step S3: Use distributed hash tree technology to perform fragmented storage processing on the hierarchical verification key to obtain distributed key fragments; and perform dynamic threshold signature processing on the distributed key fragments based on the threshold signature protocol to obtain threshold signature key fragments.

[0027] Step S4: Periodically adjust the weights of the threshold signature key fragments using a dynamic weight update algorithm to obtain updated weight key fragments; perform non-interactive verification processing on the updated weight key fragments using a zero-knowledge proof protocol to obtain verified key fragments.

[0028] Step S5: Anonymously revoke the verified key fragments using the revocable ring signature algorithm to obtain the revocation identifier key; and then use a secure erasure protocol to quantum-safely destroy the revocation identifier key to obtain the final key management result.

[0029] Example 1: In the specific implementation of step S1, the operation is further refined. First, step S11 is executed, utilizing the lattice basis generation function. The initial security parameters are processed using lattice basis construction. These initial security parameters, such as the modulus in the example above, are considered. Dimension The error distribution is Gaussian. .pass Function operations yield lattice bases. .

[0030] Next, proceed to step S12, based on the lattice basis output by the lattice basis generation function. Fault-tolerant coding techniques, such as Hamming codes, can be used for fault-tolerant coding. The generator matrix of Hamming codes is... , for Geki Encode the lattice base to obtain the encoded lattice base. This is the noise-resistant quantum key.

[0031] Step S13, using a random sampling algorithm From noise-resistant quantum key Extract the basic key components. Assume the sampling seed of the random sampling algorithm is... ,pass Function, from Randomly select some elements to obtain the basic key component set. .

[0032] Finally, step S14 is executed, using the linear combination algorithm. For the basic key set Perform linear superposition. The linear combination coefficient vector is... ,pass Function to generate the final noise-resistant quantum key .

[0033] Example 2: For step S2, in actual operation, step S21 is performed first. A system of multivariable polynomial equations is constructed, and the degree of each polynomial is set to 1. The number of variables is The polynomial coefficient matrix is ​​generated using a random coefficient generation algorithm. ,matrix elements in ( ; All of these are values ​​randomly generated within a specific range.

[0034] Then proceed to step S22, which involves resolving the noise-resistant quantum key. The input variables are mapped to a system of multivariable polynomial equations. Assume a noise-resistant quantum key distribution. After some transformation, the input variable vector is obtained. Substitute it into the system of equations In the middle, by solving the system of equations Obtain the multivariate encryption key .

[0035] The next step is S23, which uses a hash chain structure to encrypt the multivariate encryption key. Perform layer-by-layer hash binding. The function for generating the hash chain structure is: ,in, For the first The hash value of the layer. In this embodiment, it is assumed that the hash chain is built starting from the first layer, with the initial value... ; For the first The multivariate encryption key components of the layer, here the multivariate encryption key It can be divided into multiple components according to certain rules, such as , in turn serving as the layers ; This represents the XOR operation, which performs bitwise operations between the hash value of the previous layer and the key component of the current layer, increasing the complexity of the hash value. Collision-resistant hash functions, such as SHA-256, guarantee an extremely low probability of different inputs producing different hash values, thus improving security. Layered verification keys are generated through layer-by-layer computation. .

[0036] Finally, step S24 is executed to verify the chain generation algorithm. For hierarchical verification keys Perform chained signature processing. Assume the signature algorithm is... The private key is ,pass The function generates a verifiable key hash chain. .

[0037] Example 3: In the implementation of step S3, step S31 is performed first. Distributed hash tree technology, such as Merkle tree technology, is used to hierarchically verify the key. Divided into Each key is sharded. The Merkle tree constructs a tree structure by hashing the data, using the hierarchical verification keys as leaf node data. After layer-by-layer hash calculations, the root node hash value is finally obtained, which also realizes the sharding of the data.

[0038] Next, step S32 is executed to define the minimum signature threshold based on the threshold signature protocol. This requires at least two key fragments to jointly generate a valid signature. This is to improve the flexibility of key usage while ensuring security, and to prevent the loss of a single key fragment from causing the signature to fail to be generated.

[0039] Then proceed to step S33, using the Lagrange interpolation algorithm. Polynomial reconstruction processing is performed on these four key fragments.

[0040] Assume these 4 keys are fragmented as follows: ,pass The function obtains the threshold signature key fragments. .

[0041] Finally, in step S34, the fragmentation verification function is used. Each threshold signature key fragment undergoes independent validity verification. For the first In this embodiment, the verification value of each fragment is... ; For the first The signature component of each fragment is a portion of the data related to the key fragment during the signing process; The value of the Lagrange polynomial at 0 is given by the Lagrange polynomial, which is generated based on the coordinates of the key fragments. For large prime numbers, assume It is used to ensure the uniqueness and security of the calculation results, preventing problems such as hash collisions. The validity of each threshold signature key fragment is determined by calculating a verification value and comparing it with a preset correct value.

[0042] Example 4: In the specific operation of step S4, step S41 is performed first. A dynamic weight update function is constructed. ,in, For the first The weight of each slice, Corresponding to different key fragment numbers; Historical usage frequency is calculated by counting the number of times each key fragment has been used in past encryption or signature operations and combining this with the total number of operations. Trustworthiness can be assessed and scored based on factors such as the reliability of the key fragment's source and its stability during use. and For dynamic adjustment coefficients, assume , These are used to adjust the relative importance of historical usage frequency and trust score in the weighting calculation. The weight value for each key fragment is calculated using this function.

[0043] Next, step S42 is executed, using the weighted average algorithm. The weight values ​​are normalized. Assume the weight vector obtained through the dynamic weight update function is... ,pass The function yields the updated weight allocation scheme. This ensures that the sum of all weight values ​​is 1, guaranteeing the rationality and effectiveness of the weights.

[0044] Then proceed to step S43, based on the non-interactive zero-knowledge proof protocol. Generate verification proofs for each key fragment. Assume the key fragments are... ,pass Function to generate verification proof This proof can demonstrate the validity and legitimacy of a key fragment without revealing its specific contents.

[0045] Finally, step S44 is executed to prove the aggregation algorithm. Aggregate all verification proofs into a global verification result. Assume the set of all verification proofs is... ,pass Function to generate post-verification key fragments .

[0046] Example 5: In the implementation of step S5, step S51 is performed first. A revocable ring signature algorithm, such as an identity-based revocable ring signature algorithm, is used to generate a ring signature containing a revocation tag. Assume the number of ring members... When generating a ring signature, each ring member has its own private key. and public key Through the revocable ring signature algorithm The input ring members' private key sets, public key sets, and the message to be signed. Generate a ring signature containing the revocation tag. .

[0047] Next, step S52 is executed, using the anonymous undo function. The key fragment to be destroyed is identified by the revocation tag. Assume the revocation tag is... ,pass The function finds the corresponding key fragment to be destroyed in the ring signature. .

[0048] Then, in step S53, the identifier fragments are overwritten and randomized multiple times based on a quantum-safe erasure protocol. The execution steps of this protocol are as follows: First, step S531 is performed, which involves at least three full-disk random data overwrites on the key storage medium. Assuming the storage medium is a hard disk, randomly generated data blocks are written to the hard disk, with each write containing different data, overwriting the original area storing the key fragments. This operation is performed three times, thus initially destroying the original key fragment data.

[0049] Next, step S532 is executed, using a quantum random number generator to generate a truly random number sequence and replace the original stored content. The quantum random number generator generates a completely random number sequence based on the principles of quantum mechanics. Assume the generated random number sequence is... This data is then written into the storage key fragment area, further corrupting the original data.

[0050] Finally, step S533 is executed, using a physical damage detection algorithm. Verify whether the medium meets the preset entropy threshold. Assume the preset entropy threshold is... ,pass The function detects the entropy value of the storage medium. If the entropy value reaches or exceeds the threshold, the medium is considered to meet the requirements, and the original key fragmentation information is no longer recoverable.

[0051] Finally, step S54 is executed, utilizing the erase verification function. An entropy check is performed on the destroyed storage area to confirm the integrity of the destruction. Assume the destroyed storage area is... ,pass The function calculates the entropy value of the region and compares it with the preset ideal entropy value. If the two are close, the integrity of the destruction is confirmed, and the final key management result is obtained.

[0052] Example 6: Further elaboration on step S11 within step S1. When constructing the lattice basis for the initial security parameters using the lattice basis generating function, the lattice basis generating function can be implemented based on the Gaussian sampling algorithm. Using the Gaussian sampling function... For example, it is based on a given modulus. Dimensions and error distribution Perform a sampling operation. Assume an error distribution. The standard deviation is Using a Gaussian distribution, elements are randomly drawn from the probability space conforming to this distribution during each sampling process to construct a lattice basis vector. Through multiple samplings, a lattice basis vector is generated that satisfies the dimensionality requirement. The required set of lattice basis vectors is used to obtain the lattice basis. The modulus here This determines the range of values ​​for the sampling results. In subsequent encryption and calculation processes, all numerical operations involved are performed modulo... The computation is performed within a finite domain, ensuring its closure and security; dimension Given a fixed length for the lattice basis vectors, different dimensions can affect key strength and computational complexity; error distribution. This controls the randomness and noise characteristics of sampling. A suitable error distribution can improve the algorithm's resistance to attacks while ensuring key security.

[0053] Example 7: This section details the specific implementation of the random coefficient generation algorithm in step S21 of step S2. The random coefficient generation algorithm can be implemented based on the linear congruence method. Let the linear congruence formula be... ,in It is the currently generated random number. It is the next generated random number. , , These are pre-set parameters. They are used in generating the polynomial coefficient matrix. When, assume matrix The size is ( , First, select a suitable initial value. ,For example ,parameter , , Random numbers are generated sequentially using the linear congruence formula, and these random numbers are then filled into the polynomial coefficient matrix according to the row and column order of the matrix. The random coefficients generated in this way possess a certain degree of randomness and unpredictability, which meets the requirement of multivariate polynomial encryption algorithms for coefficient randomness, thus enhancing encryption security. In subsequent multivariate polynomial encryption processes, these random coefficients interact with the input variables, making the encryption result more complex and difficult to crack.

[0054] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0055] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for key management optimization based on post-quantum cryptographic algorithms, characterized in that, Includes the following steps: Step S1: The initial security parameters are constructed using a lattice-based key generation algorithm to obtain the post-quantum key generation basis; and the post-quantum key generation basis is then subjected to fault-tolerant coding techniques to obtain a noise-resistant post-quantum key. Specifically, this includes the following steps: Step S11: Use a lattice basis generating function to construct a lattice basis for the initial security parameters, wherein the initial security parameters include the modulus, dimension, and error distribution; Step S12: Based on the lattice basis output by the lattice basis generation function, the lattice basis is subjected to fault-tolerant coding processing using fault-tolerant coding technology to obtain a noise-resistant quantum key; Step S13: Extract the basic key components from the noise-resistant quantum key using a random sampling algorithm to obtain the basic key set; Step S14: Perform linear superposition processing on the basic key set using a linear combination algorithm to generate the final noise-resistant quantum key; Step S2: Apply a multivariate polynomial encryption algorithm to the noise-resistant quantum key using dynamic polynomial mapping to obtain a multivariate encryption key; then apply a hash chain structure to the multivariate encryption key using layered binding to obtain a layered verification key. This specifically includes the following steps: Step S21: Construct a system of multivariable polynomial equations and generate the polynomial coefficient matrix using a random coefficient generation algorithm; Step S22: Map the noise-resistant quantum key to the input variables of the multivariable polynomial equation system, and obtain the multivariable encryption key by solving the equation system; Step S23: Use a hash chain structure to perform layer-by-layer hash binding on the multivariate encryption key to generate a layered verification key; Step S24: Perform chained signature processing on the hierarchical verification key using the verification chain generation algorithm to obtain a verifiable key hash chain; Step S3: The hierarchical verification key is fragmented and stored using distributed hash tree technology to obtain distributed key fragments; and dynamic threshold signature processing is performed on the distributed key fragments based on the threshold signature protocol to obtain threshold signature key fragments. This specifically includes the following steps: Step S31: Use distributed hash tree technology to divide the hierarchical verification key into m key fragments, where m≥2; Step S32: Define a minimum signature threshold t based on the threshold signature protocol, requiring at least t key fragments to jointly generate a valid signature; Step S33: Use the Lagrange interpolation algorithm to perform polynomial reconstruction processing on the m key fragments to obtain the threshold signature key fragments; Step S34: Perform independent validity verification on each threshold signature key fragment using the fragment verification function; Step S4: Periodically adjust the weights of the threshold signature key fragments using a dynamic weight update algorithm to obtain updated weight key fragments; perform non-interactive verification processing on the updated weight key fragments using a zero-knowledge proof protocol to obtain verified key fragments. This specifically includes the following steps: Step S41: Construct a dynamic weight update function to calculate the weight value of each key fragment based on historical usage frequency and fragment trust level; Step S42: Normalize the weight values ​​using a weighted average algorithm to obtain an updated weight allocation scheme; Step S43: Generate verification proofs for each key fragment based on a non-interactive zero-knowledge proof protocol; Step S44: Aggregate all verification proofs into a global verification result using a proof aggregation algorithm, and generate a post-verification key fragment; Step S5: Anonymously revoke the verified key fragments using a revocable ring signature algorithm to obtain a revocation identifier key; and then quantum-safely destroy the revocation identifier key using a secure erasure protocol to obtain the final key management result. This specifically includes the following steps: Step S51: Generate a ring signature containing a revocable tag using the revocable ring signature algorithm, where the number of ring members is n; Step S52: Identify the key fragment to be destroyed using the revocation tag via an anonymous revocation function; Step S53: Based on the quantum-safe erasure protocol, the key fragments to be destroyed are overwritten and randomized multiple times to ensure that the information is unrecoverable; Step S54: Use the erase verification function to perform entropy detection on the destroyed storage area to confirm the integrity of the destruction.

2. The method for key management optimization based on post-quantum cryptography algorithm according to claim 1, characterized in that, The function for generating the hash chain structure in step S23 is as follows: ； in, Let i be the hash value of the i-th layer. For the multivariate encryption key components of the i-th layer, H represents the XOR operation, and H is the collision-resistant hash function.

3. The key management optimization method based on post-quantum cryptography algorithm according to claim 2, characterized in that, The formula for the fragmented verification function in step S34 is as follows: ； in, The verification value for the j-th fragment. For the signature component of the i-th slice, Let p be the value of the Lagrange polynomial at 0, and p be a large prime number.

4. The key management optimization method based on post-quantum cryptography algorithm according to claim 3, characterized in that, The formula for the dynamic weight update function in step S41 is as follows: in, Let i be the weight of the i-th slice. Historical usage frequency Rate trust level and This is the dynamic adjustment coefficient.

5. The key management optimization method based on post-quantum cryptography algorithm according to claim 4, characterized in that, The execution steps of the quantum-safe erasure protocol described in step S53 include: Step S531: Perform at least three full-disk random data overwrites on the key storage medium; Step S532: Use a quantum random number generator to generate a true random number sequence and replace the original stored content; Step S533: Verify whether the medium meets the preset entropy threshold using a physical damage detection algorithm.

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