A CV-QKD security enhancement system and method based on multi-objective optimization
Patent Information
- Application Number
- CN202611145389.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-07-30
- Publication Date
- 2026-10-16
AI Technical Summary
[0005]但是，CV-QKD技术存在有限码长效应，保密增强的输入密钥需要足够长才能保证最终密钥的安全性
[0040] This invention provides a CV-QKD security enhancement system and method based on multi-objective optimization. First, the optimal key length is obtained through multi-objective optimization, which initially achieves adaptive input key length. Then, by constructing a Toeplitz matrix and performing group processing on the key and the Toeplitz matrix, the adaptive input key length capability is further improved, and the processing speed of security enhancement is accelerated, making it suitable for real-time encryption applications.
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Figure CN122932972A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of quantum communication and quantum network technology, specifically to a CV-QKD security enhancement system and method based on multi-objective optimization. Background Technology
[0002] Continuous-variable quantum key distribution (CV-QKD) utilizes the continuous nature of quantum states for information transmission, ensuring key security even in the event of eavesdropping. However, in practical applications, CV-QKD technology faces several challenges, particularly regarding channel noise, eavesdropping attacks, and system performance. Therefore, post-processing is necessary to enhance key security.
[0003] Post-processing mainly includes basis vector alignment, parameter estimation, data reconciliation, and security enhancement; among these, data reconciliation and security enhancement are particularly crucial. After the data reconciliation process, both communicating parties possess an identical key string. However, a potential eavesdropper, Eve, may also obtain a data sequence containing partial information from the key string. To remove the information stolen by Eve from the identical data sequence obtained by both parties, further processing through security enhancement is required. As the final step in post-processing, the processing speed of security enhancement determines the actual key rate.
[0004] Currently, security enhancement typically involves multiplying a Toeplitz matrix by a long key string to obtain a shorter key string. This sacrifices a portion of information shared by both communicating parties, exponentially reducing the amount of information an eavesdropper can obtain, ultimately enabling Alice and Bob to share an unconditionally secure key.
[0005] However, CV-QKD technology suffers from the finite code length effect, requiring sufficiently long input keys for security enhancement to guarantee the security of the final key. The longer the input key, the larger the Toeplitz matrix becomes. Implementing large matrix multiplication operations on resource-constrained FPGAs is challenging and also limits the processing speed of security enhancement. Summary of the Invention
[0006] To address the limitation in processing speed for security enhancement in current CV-QKD technology, this invention provides a CV-QKD security enhancement system and method based on multi-objective optimization.
[0007] To achieve the above objectives, the technical solution adopted by the present invention is as follows:
[0008] A CV-QKD security enhancement system based on multi-objective optimization includes a key length detection module, a multi-objective optimization module, a matrix generation module, a first processing module, and a second processing module; wherein,
[0009] The key length detection module is used to obtain the key after data coordination as the first key and detect the length L of the first key;
[0010] The multi-objective optimization module is used to perform multi-objective optimization on the length L to obtain the optimal key length L';
[0011] The matrix generation module is used to generate the Toeplitz matrix;
[0012] The first processing module is used to divide the first key into a second key of length L';
[0013] The second processing module is used to divide the second key and the Toeplitz matrix into p blocks (L' is divisible by p), corresponding to p groups of third keys and Toeplitz submatrices; to perform matrix multiplication on each group of third keys and Toeplitz submatrices to obtain p groups of results; and to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key.
[0014] In the above scheme, the optimal key length is first obtained through multi-objective optimization, which initially achieves adaptive input key length. Then, by constructing a Toeplitz matrix and grouping the key and the Toeplitz matrix, the adaptive input key length capability is further improved, the processing speed of security enhancement is accelerated, and it is suitable for real-time encryption applications.
[0015] Preferably, the multi-objective optimization module obtains the optimal key length L' through the particle swarm optimization algorithm; wherein, the fitness function in the particle swarm optimization algorithm is affected by multiple optimization objectives.
[0016] Preferably, the optimization objectives include minimizing the security enhancement offset factor, minimizing the amount of information that an eavesdropper may steal, and maximizing the hardware processing bandwidth.
[0017] Preferably, the fitness function as follows:
[0018]
[0019] in, for The weighting coefficients, The objective function for optimizing the offset factor A to enhance secrecy; for The weighting coefficients, Let I be the objective function for optimizing the amount of information I that the eavesdropper might steal; for The weighting coefficients, The objective function for optimizing the hardware processing bandwidth B is...
[0020] Preferably, the first processing module includes a key buffer pool, an NLFSR initialization module, and an NLFSR calculation module; wherein,
[0021] The key buffer pool is used to divide the first key into a second key of length L', and to store the first key and the second key.
[0022] The NLFSR initialization module is used to obtain a first key from the key buffer pool as a seed key, generate initialization information based on the seed key, and update the state of the NLFSR based on the state update signal fed back by the NLFSR calculation module.
[0023] The NLFSR calculation module is used to receive initialization information from the NLFSR initialization module, set the clock period to the optimal key length L', calculate and generate one output bit after each clock cycle until L' output bits are generated; and feed back a status update signal to the NLFSR initialization module.
[0024] Preferably, the Toeplitz matrix is an L'×L' dimensional Toeplitz matrix.
[0025] Preferably, the matrix generation module receives L' output bits generated by the NLFSR calculation module to form the first row of data of the Toeplitz matrix, and then performs a shift operation based on the first row of data to fill the subsequent rows, thereby generating an L'×L' dimensional Toeplitz matrix.
[0026] Preferably, the second processing module includes a grouping module, a matrix multiplication module, and a modulo-2 addition module; wherein,
[0027] The grouping module is used to divide the second key and the Toeplitz matrix into p blocks respectively, thereby obtaining p groups of the third key and the Toeplitz sub-matrix.
[0028] The matrix multiplication module is used to perform matrix multiplication operations on each group of third keys and Toeplitz submatrices to obtain p groups of results;
[0029] The modulo-2 addition module is used to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key.
[0030] Preferably, the number of columns in the Toeplitz submatrix is L'.
[0031] A CV-QKD security enhancement method based on multi-objective optimization, implemented based on the aforementioned CV-QKD security enhancement system based on multi-objective optimization, is characterized by comprising the following steps:
[0032] S1: Obtain the key after data coordination as the first key, and detect the length L of the first key;
[0033] S2: Perform multi-objective optimization on the length L to obtain the optimal key length L';
[0034] S3: Divide the first key into a second key of length L';
[0035] Generate an L'×L' dimensional Toeplitz matrix;
[0036] S4: Divide the second key and the Toeplitz matrix into p blocks respectively to obtain p groups of the third key and Toeplitz sub-matrices;
[0037] S5: Perform matrix multiplication on each group of third keys and Toeplitz submatrices to obtain p groups of results;
[0038] S6: Perform modulo-2 addition on the results of p groups, and merge the results to obtain the enhanced key.
[0039] Beneficial technical effects of the present invention:
[0040] This invention provides a CV-QKD security enhancement system and method based on multi-objective optimization. First, the optimal key length is obtained through multi-objective optimization, which initially achieves adaptive input key length. Then, by constructing a Toeplitz matrix and performing group processing on the key and the Toeplitz matrix, the adaptive input key length capability is further improved, and the processing speed of security enhancement is accelerated, making it suitable for real-time encryption applications. Attached Figure Description
[0041] Figure 1 This is a schematic diagram of the module connection of the present invention;
[0042] Figure 2 This is a flowchart illustrating the implementation steps of the technical solution of the present invention;
[0043] The module includes: 1. Key length detection module; 2. Multi-objective optimization module; 3. Matrix generation module; 4. First processing module; 41. Key buffer pool; 42. NLFSR initialization module; 43. NLFSR calculation module; 5. Second processing module; 51. Grouping module; 52. Matrix multiplication module; 53. Modulo-2 addition module. Detailed Implementation
[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments. However, the scope of protection of this invention is not limited to the specific embodiments described below.
[0045] Example 1
[0046] like Figure 1 As shown, a CV-QKD security enhancement system based on multi-objective optimization includes a key length detection module 1, a multi-objective optimization module 2, a matrix generation module 3, a first processing module 4, and a second processing module 5; wherein,
[0047] The key length detection module 1 is used to obtain the key after data coordination as the first key and detect the length L of the first key.
[0048] The multi-objective optimization module 2 is used to perform multi-objective optimization on the length L to obtain the optimal key length L'.
[0049] The matrix generation module 3 is used to generate the Toeplitz matrix;
[0050] The first processing module 4 is used to divide the first key into a second key of length L';
[0051] The second processing module 5 is used to divide the second key and the Toeplitz matrix into p blocks (L' is divisible by p) to obtain p groups of third keys and Toeplitz submatrices; to perform matrix multiplication on each group of third keys and Toeplitz submatrices to obtain p groups of results; and to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key.
[0052] More specifically, the multi-objective optimization module 2 obtains the optimal key length L' through the particle swarm optimization algorithm; wherein, the fitness function in the particle swarm optimization algorithm is affected by multiple optimization objectives.
[0053] More specifically, the optimization objectives include minimizing the security enhancement offset factor, minimizing the amount of information that an eavesdropper may steal, and maximizing hardware processing bandwidth.
[0054] More specifically, the fitness function as follows:
[0055]
[0056] in, for The weighting coefficients, The objective function for optimizing the offset factor A to enhance secrecy; for The weighting coefficients, Let I be the objective function for optimizing the amount of information I that the eavesdropper might steal; for The weighting coefficients, The objective function for optimizing the hardware processing bandwidth B is...
[0057] More specifically, the first processing module 4 includes a key buffer pool 41, an NLFSR initialization module 42, and an NLFSR calculation module 43; wherein, NLFSR stands for Nonlinear feedback shift register.
[0058] The key buffer pool 41 is used to divide the first key into a second key of length L', and to store the first key and the second key.
[0059] The NLFSR initialization module 42 is used to obtain a first key from the key buffer pool 41 as a seed key, generate initialization information based on the seed key, and update the state of the NLFSR based on the state update signal fed back by the NLFSR calculation module 43.
[0060] The NLFSR calculation module 43 is used to receive initialization information from the NLFSR initialization module 42, set the clock period to the optimal key length L', calculate and generate one output bit after each clock cycle until L' output bits are generated; and feed back a status update signal to the NLFSR initialization module.
[0061] More specifically, the Toeplitz matrix is an L'×L' dimensional Toeplitz matrix.
[0062] More specifically, the matrix generation module 3 receives L' output bits generated by the NLFSR calculation module 43 to form the first row of data of the Toeplitz matrix, and then performs a shift operation based on the first row of data to fill the subsequent rows, thereby generating an L'×L' dimensional Toeplitz matrix.
[0063] More specifically, the second processing module 5 includes a grouping module 51, a matrix multiplication module 52, and a modulo-2 addition module 53; wherein,
[0064] The grouping module 51 is used to divide the second key and the Toeplitz matrix into p blocks respectively, thereby obtaining p groups of third keys and Toeplitz sub-matrices.
[0065] The matrix multiplication module 52 is used to perform matrix multiplication operations on each group of third keys and Toeplitz submatrices to obtain p groups of results;
[0066] The modulo-2 addition module 53 is used to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key.
[0067] More specifically, the Toeplitz submatrix has L' columns.
[0068] In the specific implementation process, the Toeplitz matrix is divided by rows while the columns remain unchanged, resulting in an L' / p*L' dimensional Toeplitz submatrix.
[0069] In the specific implementation process, the optimal key length is first obtained through multi-objective optimization, initially achieving adaptive input key length. Then, by constructing a Toeplitz matrix and grouping the key and the Toeplitz matrix, the adaptive input key length capability is further improved, accelerating the processing speed of security enhancement. At the same time, by using NLFSR to construct the Toeplitz matrix, the storage resource consumption is significantly reduced. Moreover, the nonlinear characteristics of NLFSR make the generated sequence more random and difficult to crack, effectively improving the randomness of the Toeplitz matrix and the security of the final key, making it suitable for real-time encryption applications.
[0070] Example 2
[0071] like Figure 2 As shown, a CV-QKD security enhancement method based on multi-objective optimization is implemented based on the aforementioned CV-QKD security enhancement system based on multi-objective optimization. Its features include the following steps:
[0072] S1: Obtain the key after data coordination as the first key, and detect the length L of the first key;
[0073] S2: Perform multi-objective optimization on the length L to obtain the optimal key length L';
[0074] S3: Divide the first key into a second key of length L';
[0075] Generate an L'×L' dimensional Toeplitz matrix;
[0076] S4: Divide the second key and the Toeplitz matrix into p blocks respectively to obtain p groups of the third key and Toeplitz sub-matrices;
[0077] S5: Perform matrix multiplication on each group of third keys and Toeplitz submatrices to obtain p groups of results;
[0078] S6: Perform modulo-2 addition on the results of p groups, and merge the results to obtain the enhanced key.
[0079] More specifically, in step S2, the length L is optimized using a particle swarm optimization algorithm to obtain the optimal key length L'. The specific process is as follows:
[0080] S2.1: Initialize the particle swarm: Set the initial position x0 and initial velocity v0 of the particles;
[0081] Initialize the individual extremum of each particle, and set the global extremum;
[0082] S2.2: Calculate particle fitness: based on the particle's current position and fitness function. Calculate the fitness value for each particle;
[0083] S2.3: Update Individual Extreme Value: If the fitness value of a particle's current position is better than its individual extreme value, then update the individual extreme value. ;
[0084] S2.4: Update Global Minimum: If the fitness value of the particle's current position is better than the global minimum, then update the global minimum. ;
[0085] S2.5: Particle velocity and position update: Calculate the new velocity using the velocity and position update formula;
[0086] The speed update formula is ;
[0087] The position update formula is ,
[0088] in, For different learning factors, w is the inertia weight, and t is the current iteration number. Different random numbers;
[0089] S2.6: Check the termination condition: If the fitness value calculated in two consecutive iterations does not change or the preset maximum number of iterations is reached, then end the iteration and output the optimal key length L'; otherwise, return to S2.2 to continue the iteration.
[0090] Based on the disclosure and teachings of the foregoing specification, those skilled in the art can make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the invention should also fall within the protection scope of the claims of the present invention. Furthermore, although some specific terms are used in this specification, these terms are only for convenience of explanation and do not constitute any limitation on the present invention.
Claims
1. A CV-QKD security enhancement system based on multi-objective optimization, characterized in that, It includes a key length detection module, a multi-objective optimization module, a matrix generation module, a first processing module, and a second processing module; among which, The key length detection module is used to obtain the key after data coordination as the first key and detect the length L of the first key; The multi-objective optimization module is used to perform multi-objective optimization on the length L to obtain the optimal key length L'; The matrix generation module is used to generate the Toeplitz matrix; The first processing module is used to divide the first key into a second key of length L'; The second processing module is used to divide the second key and the Toeplitz matrix into p blocks respectively, thereby obtaining p groups of third keys and Toeplitz sub-matrices; to perform matrix multiplication on each group of third keys and Toeplitz sub-matrices to obtain p groups of results; and to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key; wherein L' is divisible by p.
2. The CV-QKD security enhancement system based on multi-objective optimization according to claim 1, characterized in that, The multi-objective optimization module obtains the optimal key length L' through the particle swarm optimization algorithm; wherein, the fitness function in the particle swarm optimization algorithm is affected by multiple optimization objectives.
3. The CV-QKD security enhancement system based on multi-objective optimization according to claim 2, characterized in that, The optimization objectives include minimizing the security enhancement offset factor, minimizing the amount of information that an eavesdropper may steal, and maximizing hardware processing bandwidth.
4. The CV-QKD security enhancement system based on multi-objective optimization according to claim 3, characterized in that, The fitness function as follows: in, for The weighting coefficients, The objective function for optimizing the offset factor A to enhance secrecy; for The weighting coefficients, Let I be the objective function for optimizing the amount of information I that the eavesdropper might steal; for The weighting coefficients, The objective function for optimizing the hardware processing bandwidth B is...
5. The CV-QKD security enhancement system based on multi-objective optimization according to claim 1, characterized in that, The first processing module includes a key buffer pool, an NLFSR initialization module, and an NLFSR calculation module; wherein, The key buffer pool is used to divide the first key into a second key of length L', and to store the first key and the second key. The NLFSR initialization module is used to obtain a first key from the key buffer pool as a seed key, generate initialization information based on the seed key, and update the state of the NLFSR based on the state update signal fed back by the NLFSR calculation module. The NLFSR calculation module is used to receive initialization information from the NLFSR initialization module, set the clock period to the optimal key length L', calculate and generate one output bit after each clock cycle until L' output bits are generated; and feed back a status update signal to the NLFSR initialization module.
6. The CV-QKD security enhancement system based on multi-objective optimization according to claim 1, characterized in that, The Toeplitz matrix is an L'×L' dimensional Toeplitz matrix.
7. The CV-QKD security enhancement system based on multi-objective optimization according to claim 6, characterized in that, The matrix generation module receives L' output bits generated by the NLFSR calculation module to form the first row of data of the Toeplitz matrix. Then, it performs a shift operation based on the first row of data to fill the subsequent rows, thereby generating an L'×L' dimensional Toeplitz matrix.
8. The CV-QKD security enhancement system based on multi-objective optimization according to claim 1, characterized in that, The second processing module includes a grouping module, a matrix multiplication module, and a modulo-2 addition module; wherein, The grouping module is used to divide the second key and the Toeplitz matrix into p blocks respectively, thereby obtaining p groups of the third key and the Toeplitz sub-matrix. The matrix multiplication module is used to perform matrix multiplication operations on each group of third keys and Toeplitz submatrices to obtain p groups of results; The modulo-2 addition module is used to perform modulo-2 addition on the p groups of results and merge the results to obtain the enhanced key.
9. A CV-QKD security enhancement system based on multi-objective optimization according to claim 8, characterized in that, The Toeplitz submatrix has L' columns.
10. A CV-QKD security enhancement method for a CV-QKD security enhancement system based on multi-objective optimization according to any one of claims 1-9, characterized in that, Includes the following steps: S1: Obtain the key after data coordination as the first key, and detect the length L of the first key; S2: Perform multi-objective optimization on the length L to obtain the optimal key length L'; S3: Divide the first key into a second key of length L'; Generate an L'×L' dimensional Toeplitz matrix; S4: Divide the second key and the Toeplitz matrix into p blocks respectively to obtain p groups of the third key and Toeplitz sub-matrices; S5: Perform matrix multiplication on each group of third keys and Toeplitz submatrices to obtain p groups of results; S6: Perform modulo-2 addition on the results of p groups, and merge the results to obtain the enhanced key.