Intelligent user data encryption protection method and system

Abstract

The invention discloses an intelligent user data encryption protection method and system. The method comprises the steps of presetting, confusion processing, hybrid mapping, encryption processing and encryption optimization processing. The invention belongs to the technical field of data protection, and particularly relates to an intelligent user data encryption protection method and system.According to the scheme, unpredictability of data protection is enhanced through multi-level encryption and confusion processing, and good balance is found between efficiency and safety through XOR diffusion and hybrid mapping; different levels of measurement are carried out on local security and global security, so that the diversity and complexity of an encryption process are increased; through selection based on fitness values and a non-fixed multi-pairing mechanism, the overall encryption strength is improved; an aging correction mechanism is introduced, and the diversity of encrypted sequences is enhanced by dynamically generating a common allele set; a file set is adopted to store all potential optimal solutions, so that the security and the attack resistance of the ciphertext are improved; and finally, the data encryption protection effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of data protection, and specifically refers to an intelligent user data encryption protection method and system. Background Art

[0002] The user data encryption protection method refers to a series of technologies and algorithms designed to encrypt sensitive user data to ensure that the data is not accessed, modified, or stolen by unauthorized third parties during storage, transmission, or use. However, general user data encryption protection methods have problems such as excessive computational complexity, poor ability to process large-scale data, vulnerability to pattern analysis attacks, resulting in low encryption protection security; general user data encryption protection methods use fixed encryption methods, lack real-time adaptation to ciphertext changes, are vulnerable to differential attacks, resulting in poor data encryption protection effects. Summary of the Invention

[0003] In view of the above situation, to overcome the defects of the prior art, the present invention provides an intelligent user data encryption protection method. Aiming at the problems of excessive computational complexity, poor ability to process large-scale data, vulnerability to pattern analysis attacks, and resulting in low encryption protection security in general user data encryption protection methods, this solution enhances the complexity and unpredictability of data protection through multi-level encryption and confusion processing. During the encryption process, through the steps of exclusive-or diffusion and mixed mapping, the data is gradually disrupted and diffused, significantly improving the ability to resist statistical analysis attacks and pattern analysis attacks; the elliptic curve encryption algorithm is used to reduce the computational and storage overhead, finding a good balance between efficiency and security; aiming at the problems of using fixed encryption methods, lack of real-time adaptation to ciphertext changes, vulnerability to differential attacks, and resulting in poor data encryption protection effects in general user data encryption protection methods, this solution measures local security and global security at different levels, increasing the diversity and complexity of the encryption process; through fitness value-based selection and non-fixed multiple pairing mechanisms, continuously reducing encryption weaknesses and improving the overall encryption strength; introducing an aging correction mechanism to continuously improve the encryption effect in long-term iterations; enhancing the diversity of the encryption sequence by dynamically generating a common allele set; using an archive set to store all potential optimal solutions to ensure that the global optimal ciphertext arrangement can be continuously updated in multiple iteration cycles, enhancing the security and anti-attack ability of the ciphertext; ultimately improving the data encryption protection effect.

[0004] The technical solution adopted by the present invention is as follows: The intelligent user data encryption protection method provided by the present invention includes the following steps:

[0005] Step S1: Preset;

[0006] Step S2: Confusion processing;

[0007] Step S3: Hybrid mapping;

[0008] Step S4: Encryption processing;

[0009] Step S5: Encryption optimization processing.

[0010] Furthermore, in step S1, the presetting is to obtain the user data to be encrypted. Let the user data to be encrypted be a binary stream, expressed as: ; where D is the original data sequence of the user to be encrypted; L is the length; and are the first and the L-th original data respectively.

[0011] Furthermore, in step S2, the confusion processing is to use the numerical product to solve the Lorenz system iteratively for L times to obtain the data at L time points, and use the Rossler attractor to have a set of three-dimensional vectors at each time point ; expressed as: ; where, , and are the time derivatives of variables X, Y, and Z in the Lorenz system respectively; A, B, and C are behavior parameters; normalized and mapped to the index [1, L], expressed as: ; where max(X) and min(X) are the maximum and minimum values of all respectively; is the mapped index, representing the permutation order of the positions after the Lorenz system is confused, and is finally used for byte scrambling; the scrambled byte sequence, expressed as: ; where, is the byte sequence after confusion; is the original data corresponding to the index; according to the Lorenz confusion and the mapped index, the original data is scrambled to generate the confused data sequence .

[0012] Furthermore, in step S3, the hybrid mapping is to generate two sequences through the Logistic mapping and the PWLCM iteration , and introduce a dynamic adjustment mechanism; expressed as: ; ; ; ; where, and are the Logistic mapping values of the (n + 1)-th and the n-th iterations respectively; is the mapping parameter; and They are the PWLCM mapping values of the (n + 1)-th and n-th iterations respectively; P1 is the mapping threshold; is to introduce random noise; and is the dynamic adjustment factor; and is the maximum adjustment factor; and is the minimum adjustment factor; is the entropy value; mixed normalization, expressed as: ; where is the normalized sequence after mixing; XOR diffusion, expressed as: ; where is the byte after XOR diffusion; is the value of the i-th after mixed normalization.

[0013] Furthermore, in step S4, the encryption process specifically includes the following steps:

[0014] Step S41: Select an elliptic curve equation, expressed as: ; ; where a and b are the parameters of the elliptic curve; p is the prime modulus; x and y are the coordinates on the elliptic curve; E is the elliptic curve;

[0015] Step S42: Generate the private key and public key, expressed as: ; ; where K is the private key; P is the public key; G is the base point of the elliptic curve; Step S43: Map the byte to the curve point; Define the mapping function , ; denoted as ; where is the byte after mapping , which is mapped to a point on the elliptic curve; is the set of elliptic curve points defined on ; O is the infinite point of the curve; Step S44: For each random number : ; ; ; ; where is the randomly selected number ; is the elliptic curve point calculated based on , which participates in the encryption process; is the product of the public keys; is the encrypted ciphertext part; is the ciphertext pair obtained after encryption; the ciphertext sequence obtained after ECC encryption is regarded as a gene string of length L; and encryption optimization processing is performed.

[0016] Furthermore, in step S5, the encryption optimization processing specifically includes the following steps:

[0017] Step S51: Each individual u is a possible ciphertext permutation scheme; the performance of the individual is evaluated; the adjacent correlation coefficient sequence is calculated , and the average is taken as ; a three-layer metric is designed; the total fitness value of the individual is expressed as: : ; where u is the individual index; k is the metric adjustment weight; is the underlying local metric, measuring the correlation of adjacent ciphertexts; is the middle-layer global metric, measuring NPCR and UACI; is the top-layer global metric, measuring the entropy value; is the Pareto front set; is the distance between the individual and the optimal value; the definition principles of the middle-layer global metric and the top-layer global metric are the same as those of the underlying local metric; is the maximum value among the distances between all individuals and the optimal value;

[0018] Step S52: Establish an aging correction mechanism; let the population size , update individuals each time, the average lifespan , the aging starting point , the lifespan upper limit ; the final individual fitness value after aging correction is expressed as:

[0019] ; where t is the current survival generation of the individual; is the aging starting generation;

[0020] Step S53: Non-fixed multiple pairing; calculate the selected pairing probability , which is expressed as: ; where M is the current population size; v is the population individual index; randomly generate pairs each time, allowing repetition; each pair produces only 1 offspring; for each position, the offspring gene has a 50% probability of inheriting the father and a 50% probability of inheriting the mother;

[0021] Step S54: Dynamic common allele set; for each gene locus, take the top T values that appear most frequently among all individuals as the common set; let the overall mutation probability be , the probability of falling into the common set is , the size of the common set is T, and the size outside the set is ; then the mutation probability of each value in the set is ; the mutation probability of each value outside the set is ;

[0022] Step S55: Archive set maintenance; calculate the elimination index , expressed as: ; where is the corresponding index of the individual in the previous generation's archive The fitness value of the archived individual; each generation eliminates individuals in ascending order ; individuals that are eliminated but belong to the Pareto front of the current population are added to the archive; the Pareto status of the individuals in the archive is re-evaluated every generation, and those that no longer meet the criteria are removed; at the end, the archive is the global optimal Pareto ciphertext permutation set;

[0023] Step S56: After iterating G generations, output the set of ciphertext permutations with the best performance in the archive set as the final enhanced ciphertext, thereby realizing data encryption protection.

[0024] The intelligent user data encryption protection system provided by the present invention includes a presetting module, a confusion processing module, a hybrid mapping module, an encryption processing module, and an encryption optimization processing module;

[0025] The presetting module represents the user data to be encrypted as a binary stream sequence;

[0026] The confusion processing module uses the Lorenz system to generate a confusion sequence through numerical integration and maps the original data to a new index position;

[0027] The hybrid mapping module generates a hybrid sequence through Logistic mapping and PWLCM iteration and performs XOR diffusion;

[0028] The encryption processing module uses the elliptic curve encryption algorithm to generate a public key and a private key, and maps the encrypted data points to an elliptic curve through mapping to complete the encryption process;

[0029] The encryption optimization processing module outputs the optimal encryption permutation scheme by optimizing the encryption permutation.

[0030] The beneficial effects achieved by the present invention using the above solution are as follows:

[0031] (1) Aiming at the problems that the general user data encryption protection method has excessive computational complexity, poor ability to process large-scale data, is vulnerable to pattern analysis attacks, and thus leads to low security of encryption protection, this solution enhances the complexity and unpredictability of data protection through multi-level encryption and confusion processing. During the encryption process, through the steps of exclusive-or diffusion and hybrid mapping, the data is gradually disrupted and diffused, significantly improving the ability to resist statistical analysis attacks and pattern analysis attacks; the elliptic curve encryption algorithm is used to reduce the computational and storage overhead, finding a good balance between efficiency and security.

[0032] (2) Aiming at the problems that the general user data encryption protection method uses a fixed encryption method, lacks real-time adaptation to ciphertext changes, is vulnerable to differential attacks, and thus leads to poor data encryption protection effect, this solution measures local security and global security at different levels, increasing the diversity and complexity of the encryption process; through selection based on fitness values and a non-fixed multiple pairing mechanism, continuously reducing encryption weaknesses and improving the overall encryption strength; introducing an aging correction mechanism to continuously improve the encryption effect in long-term iterations; enhancing the diversity of the encryption sequence by dynamically generating a common allele set; using an archive set to store all potential optimal solutions to ensure that the global optimal ciphertext arrangement can be continuously updated in multiple iteration cycles, enhancing the security and anti-attack ability of the ciphertext; ultimately improving the data encryption protection effect. Brief Description of the Drawings

[0033] Figure 1 It is a schematic flowchart of the intelligent user data encryption protection method provided by the present invention;

[0034] Figure 2 It is a schematic flowchart of the intelligent user data encryption protection system.

[0035] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation to the present invention. Detailed Embodiments

[0036] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments; based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0037] In the description of the present invention, it should be understood that the terms "upper", "lower", "front", "rear", "left", "right", "top", "bottom", "inner", "outer", etc. indicating the orientation or positional relationship are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention.

[0038] Embodiment 1. Refer to Figure 1 , the intelligent user data encryption and protection method provided by the present invention includes the following steps:

[0039] Step S1: Preset; represent the user data to be encrypted as a binary stream sequence;

[0040] Step S2: Confusion processing; use the Lorenz system to generate a confusion sequence through numerical integration, and map the original data to a new index position;

[0041] Step S3: Hybrid mapping; generate a hybrid sequence through Logistic mapping and PWLCM iteration, and perform exclusive-or diffusion;

[0042] Step S4: Encryption processing; use the elliptic curve encryption algorithm to generate a public key and a private key, and map the encrypted data points to the elliptic curve through mapping to complete the encryption process;

[0043] Step S5: Encryption optimization processing; output the optimal encryption arrangement scheme by optimizing the encryption arrangement.

[0044] Embodiment 2. Refer to Figure 1 , based on the above embodiment, in step S1, the preset is to obtain the user data to be encrypted. Let the user data to be encrypted be a binary stream, expressed as: ; where D is the original data sequence of the user to be encrypted; L is the length; and are the first and the L-th original data respectively.

[0045] Embodiment 3. Refer to Figure 1 , based on the above embodiment, in step S2, the confusion processing is to solve the Lorenz system by numerical integration and continuously iterate L times to obtain the data at L time points, and use the Rossler attractor to increase the oscillation frequency and chaotic characteristics. Each time point has a set of three-dimensional vectors ; expressed as: ; where , and They are the time derivatives of variables X, Y, and Z in the Lorenz system respectively; A, B, and C are behavioral parameters; they are normalized and mapped to the index [1, L], expressed as: ; where, max(X) and min(X) are the maximum and minimum values of all respectively; is the mapped index, representing the permutation order of the positions after the Lorenz system is scrambled, and is finally used for byte scrambling; the scrambled byte sequence is expressed as: ; where, is the byte sequence after scrambling; is the original data corresponding to the index; according to the Lorenz scrambling and the mapped index, the original data is scrambled to generate the scrambled data sequence .

[0046] Example 4, refer to Figure 1 , based on the above example, in step S3, the hybrid mapping generates two sequences through the Logistic mapping and the PWLCM iteration , and a dynamic adjustment mechanism is introduced to automatically adjust according to the complexity and changes of the encrypted data, improving the encryption adaptability; it is expressed as: ; ; ; ; where, and are the Logistic mapping values of the (n + 1)-th and n-th iterations respectively; is the mapping parameter; and are the PWLCM mapping values of the (n + 1)-th and n-th iterations respectively; P1 is the mapping threshold; is the introduced random noise; and are the dynamic adjustment factors; and are the maximum adjustment factors; and are the minimum adjustment factors; is the entropy value; the hybrid normalization is expressed as: ; where, is the hybridized normalized sequence; the XOR diffusion is expressed as: ; where, is the byte after XOR diffusion; is the i-th value after hybrid normalization.

[0047] Example 5, refer to Figure 1 and Figure 2 , based on the above example, in step S4, the encryption process specifically includes the following steps:

[0048] Step S41: Select an elliptic curve equation, expressed as: ; ; where a and b are the parameters of the elliptic curve; p is the prime modulus; x and y are the coordinates on the elliptic curve; E is the ellipse;

[0049] Step S42: Generate the private key and public key, expressed as: ; ; where K is the private key; P is the public key; G is the base point of the elliptic curve; Step S43: Map the byte curve points; Define the mapping function , ; Denote it as ; where is the byte after mapping , which is mapped to a point on the elliptic curve; is the set of elliptic curve points defined on ; O is the infinite point of the curve; Step S44: For each random number : ; ; ; ; where is the randomly selected number ; is the elliptic curve point calculated based on , which participates in the encryption process; is the product of the public keys; is the encrypted ciphertext part; is the ciphertext pair obtained after encryption; The ciphertext sequence obtained after ECC encryption is regarded as a gene string of length L; And perform encryption optimization processing.

[0050] By performing the above operations, for the general user data encryption protection method, there are problems such as excessive computational complexity, poor ability to process large-scale data, vulnerability to pattern analysis attacks, and thus low encryption protection security. This solution enhances the complexity and unpredictability of data protection through multi-level encryption and confusion processing. During the encryption process, through the XOR diffusion and mixed mapping steps, the data is gradually disrupted and diffused, significantly improving the ability to resist statistical analysis attacks and pattern analysis attacks; The elliptic curve encryption algorithm is used to reduce the computational and storage overhead, and a good balance is found between efficiency and security.

[0051] Example 6, refer to Figure 1 , based on the above example, in step S5, the encryption optimization processing specifically includes the following steps:

[0052] Step S51: Each individual u is a possible ciphertext permutation scheme; perform performance evaluation on the individuals; calculate the adjacent correlation coefficient sequence , and take the average as ; To balance the local security with low adjacent ciphertext correlation and the global security with high overall entropy, design a three-layer metric; the total fitness value of the individual is expressed as: : ; where u is the individual index; k is the metric adjustment weight; is the underlying local metric, measuring the correlation of adjacent ciphertexts; is the middle-layer global metric, measuring NPCR and UACI; is the top-layer global metric, measuring the entropy value; is the Pareto front set; is the distance between the individual and the optimal value; the definition principles of the middle-layer global metric and the top-layer global metric are the same as those of the underlying local metric; is the maximum value among the distances between all individuals and the optimal value;

[0053] Step S52: Establish an aging correction mechanism; let the population size , update individuals each iteration, the average lifespan , the aging starting point , the lifespan upper limit ; the final individual fitness value after aging correction is expressed as:

[0054] ; where t is the current survival generation of the individual; is the aging starting generation;

[0055] Step S53: Non-fixed multiple pairing; calculate the selected pairing probability , expressed as: ; where M is the current population size; v is the population individual index; randomly generate pairs each iteration, allowing repetition; each pair produces only 1 offspring; for each position, the offspring gene has a 50% probability of inheriting the paternal gene and a 50% probability of inheriting the maternal gene;

[0056] Step S54: Dynamic common allele set; for each gene locus, take the top T values that appear most frequently among all individuals as the common set; let the overall mutation probability be , the probability of falling into the common set be , the size of the common set be T, and the size outside the set be ; then the mutation probability of each value inside the set is ; the mutation probability of each value outside the set is ;

[0057] Step S55: Archive set maintenance; calculating elimination metrics , expressed as: ; where is the corresponding index of the individual in the previous generation's archive The fitness value of the archived; in each generation, according to Eliminate individuals from smallest to largest Individuals; individuals that are eliminated but belong to the Pareto front of the current population are added to the archive; in each generation, the Pareto status of the individuals in the archive is re-evaluated, and those that no longer meet the criteria are removed; at termination, the archive is the globally optimal Pareto ciphertext permutation set;

[0058] Step S56: After iterating G generations, output a set of ciphertext permutations with the smallest correlation coefficient, the largest entropy, and the optimal NPCR / UACI in the archive set as the final enhanced ciphertext, thereby achieving data encryption protection.

[0059] By performing the above operations, for the general user data encryption protection method, there is a problem that a fixed encryption method is adopted, lacking real-time adaptation to ciphertext changes, being vulnerable to differential attacks, and thus resulting in poor data encryption protection effect. In this solution, different levels of measurement are performed on local security and global security to increase the diversity and complexity of the encryption process; through fitness value-based selection and non-fixed multiple pairing mechanisms, encryption weaknesses are continuously reduced, and the overall encryption strength is improved; an aging correction mechanism is introduced to continuously enhance the encryption effect in long-term iterations; by dynamically generating a common allele set, the diversity of the encryption sequence is enhanced; an archive set is used to store all potential optimal solutions to ensure that the globally optimal ciphertext permutation can be continuously updated in multiple iteration cycles, enhancing the security and anti-attack ability of the ciphertext; ultimately improving the data encryption protection effect.

[0060] Example Seven, refer to Figure 2 , based on the above example, the intelligent user data encryption protection system provided by the present invention includes a presetting module, a confusion processing module, a hybrid mapping module, an encryption processing module, and an encryption optimization processing module;

[0061] The presetting module represents the user data to be encrypted as a binary stream sequence;

[0062] The confusion processing module uses the Lorenz system to generate a confusion sequence through numerical integration and maps the original data to a new index position;

[0063] The hybrid mapping module generates a hybrid sequence through Logistic mapping and PWLCM iteration and performs XOR diffusion;

[0064] The encryption processing module uses the elliptic curve encryption algorithm to generate a public key and a private key, and maps the encrypted data points to an elliptic curve through mapping to complete the encryption process;

[0065] The encryption optimization processing module outputs an optimal encryption arrangement scheme by optimizing the encryption arrangement.

[0066] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0067] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

[0068] The above describes the present invention and its implementation manners. Such description is not restrictive. What is shown in the drawings is only one of the implementation manners of the present invention, and the actual structure is not limited thereto. Generally speaking, if those of ordinary skill in the art are inspired by it and design similar structural manners and embodiments without creative efforts without departing from the purpose of the present invention, they shall fall within the protection scope of the present invention.

Claims

1. An intelligent user data encryption and protection method, characterized in that: The method includes the following steps: Step S1: Presetting; representing the user data to be encrypted as a binary stream sequence; Step S2: Confusion processing; using the Lorenz system to generate a confusion sequence through numerical integration and mapping the original data to a new index position; Step S3: Hybrid mapping; generating a hybrid sequence through Logistic mapping and PWLCM iteration and performing XOR diffusion; Step S4: Encryption processing; using the elliptic curve encryption algorithm to generate a public key and a private key and mapping the encrypted data points to an elliptic curve through mapping to complete the encryption process; Step S5: Encryption optimization processing; outputting an optimal encryption permutation scheme by optimizing the encryption permutation.

2. The intelligent user data encryption and protection method according to claim 1, wherein: In step S2, the confusion process is to use numerical integration to solve the Lorenz system and continuously iterate it L times to obtain data at L time points, and each time point of the Rossler attractor has a set of three-dimensional vectors ; which is expressed as: ; where , and are the time derivatives of variables X, Y, and Z in the Lorenz system respectively; A, B, and C are behavior parameters; they are normalized and mapped to the index [1, L], which is expressed as: ; where max(X) and min(X) are the maximum and minimum values of all respectively; is the mapped index, representing the permutation order of the positions after the Lorenz system is confused, and is finally used for byte scrambling; the scrambled byte sequence is expressed as: ; where is the byte sequence after confusion; is the original data corresponding to the index; according to the Lorenz confusion and the mapped index, the original data is scrambled to generate a confused data sequence .

3. The intelligent user data encryption and protection method according to claim 2, wherein: In step S3, the hybrid mapping generates two sequences through the Logistic mapping and the PWLCM iteration , and a dynamic adjustment mechanism is introduced; it is expressed as: ; ; ; ; where and are the Logistic mapping values of the (n + 1)-th and n-th iterations respectively; is the mapping parameter; and are the PWLCM mapping values of the (n + 1)-th and n-th iterations respectively; P1 is the mapping threshold; is the introduced random noise; and are the dynamic adjustment factors; and are the maximum adjustment factors; and are the minimum adjustment factors; is the entropy value; hybrid normalization is expressed as: ; where is the normalized sequence after mixing; XOR diffusion is expressed as: ; where is the byte after XOR diffusion; is the value of the i-th hybrid normalized value.

4. The intelligent user data encryption and protection method according to claim 3, wherein: In step S4, the encryption processing specifically includes the following steps: Step S41: Select an elliptic curve equation, expressed as: ; ; where a and b are parameters of the elliptic curve; p is a prime modulus; x and y are coordinates on the elliptic curve; E is the ellipse; Step S42: Private key and public key generation, expressed as: ; ; where K is the private key; P is the public key; G is the base point of the elliptic curve; Step S43: Byte curve point mapping; define a mapping function , ; denoted as ; where is the byte after mapping , which is mapped to a point on the elliptic curve; is the set of elliptic curve points defined on ; O is the infinite point of the curve Step S44: For each random number : ; ; ; ; where is a randomly selected number ; is an elliptic curve point calculated based on and participates in the encryption process; is the product of the public keys; is the encrypted ciphertext part; is the ciphertext pair obtained after encryption; The ciphertext sequence obtained after ECC encryption is regarded as a gene string of length L; and encryption optimization processing is performed.

5. The intelligent user data encryption and protection method according to claim 1, characterized in that: In step S5, the encryption optimization processing specifically includes the following steps: Step S51: Each individual u is a possible ciphertext permutation scheme; perform performance evaluation on the individuals; calculate the adjacent correlation coefficient sequence , and take the average as ; design a three-layer metric; the total fitness value of the individual is expressed as: : ; where u is the individual index; k is the metric adjustment weight; is the underlying local metric, measuring the correlation between adjacent ciphertexts; is the middle-level global metric, measuring NPCR and UACI; is the top-level global metric, measuring the entropy value; is the Pareto front set; is the distance between the individual and the optimal value; the definition principles of the middle-level global metric and the top-level global metric are the same as those of the underlying local metric; is the maximum value among the distances between all individuals and the optimal value; Step S52: Establish an aging correction mechanism; set the population size , update iteratively each time individuals, average lifespan , aging starting point , lifespan upper limit ; The final individual fitness value after aging correction is expressed as: where t is the current survival generation of the individual; is the starting generation of senescence; Step S53: Non-fixed multiple pairing; calculate the selected pairing probability , expressed as: ; where M is the current population size; v is the population individual index; randomly generate pairs each iteration, allowing repetition; each pair produces only 1 offspring; for each position, the offspring gene has a 50% probability of inheriting the father and a 50% probability of inheriting the mother; Step S54: Dynamic common allele set; Step S55: Archive set maintenance; calculating elimination metrics , expressed as: ; where is the corresponding index of the individual in the previous generation's archive the archived fitness value; in each generation, according to eliminate individuals in ascending order ; individuals that are eliminated but belong to the Pareto front of the current population are added to the archive; in each generation, re-evaluate the Pareto status of the individuals in the archive, and remove those that no longer meet the criteria; at termination, the archive is the globally optimal Pareto ciphertext permutation set; Step S56: After iterating G generations, output a set of ciphertext permutations with the optimal performance in the archive set as the final enhanced ciphertext, thereby realizing data encryption protection.

6. The intelligent user data encryption and protection method according to claim 5, wherein: In step S5, the step S54: dynamic common allele set; for each genetic locus, the top T values that appear most frequently among all individuals are used as the common set; let the overall mutation probability be , the probability of falling into the common set is , the size of the common set is T, and the size outside the set is ; then the mutation probability of each value within the set is ; the mutation probability of each value outside the set is .

7. The intelligent user data encryption and protection method according to claim 6, characterized in that: In step S1, the presetting is to obtain user data to be encrypted. Let the user data to be encrypted be a binary stream, expressed as: ; where D is the original data sequence of the user to be encrypted; L is the length; and are the first and the L-th original data respectively.

8. An intelligent user data encryption protection system for implementing the intelligent user data encryption protection method as described in any one of claims 1-7, characterized in that: It includes a presetting module, a confusion processing module, a hybrid mapping module, an encryption processing module, and an encryption optimization processing module; The presetting module represents the user data to be encrypted as a binary stream sequence; The confusion processing module uses the Lorenz system to generate a confusion sequence through numerical integration and maps the original data to a new index position; The hybrid mapping module generates a hybrid sequence through Logistic mapping and PWLCM iteration and performs XOR diffusion; The encryption processing module uses the elliptic curve encryption algorithm to generate a public key and a private key and maps the encrypted data points to an elliptic curve through mapping to complete the encryption process; The encryption optimization processing module outputs an optimal encryption permutation scheme by optimizing the encryption permutation.

Images