Data security protection method and system

Abstract

The invention discloses a data security protection method and system, and relates to the technical field of data protection, a parameter generator automatically outputs dimension parameters, modulus parameters and noise parameters, a random matrix and a secret key vector are obtained according to the dimension parameters and the modulus parameters, a public key vector is obtained through calculation of the random matrix, the secret key vector and noise, and the public key vector is stored in a database; after data needing to be encrypted is converted into a binary vector, a ciphertext is calculated in combination with a public key vector and the binary vector, data in a storage medium is encrypted through the ciphertext, and when a user needs to read the data, decryption and data recovery are carried out through a secret key vector after the ciphertext is received. The protection system depends on solving the shortest vector problem on lattices, has considerable difficulty in both classical and quantum computing environments, and can support various cryptographic applications, and the flexibility enables the security protection method to adapt to different application requirements and ensure secure storage of data.

Description

Technical Field

[0001] The present invention relates to the technical field of data protection, and in particular to a data security protection method and system. Background Art

[0002] Data security protection involves ensuring the confidentiality, integrity and availability of data during storage, transmission and processing to prevent unauthorized access, disclosure, tampering or loss.

[0003] The prior art has the following deficiencies:

[0004] 1. Traditional protection methods such as RSA and ECC (elliptic curve cryptography) rely on mathematical problems such as integer decomposition and discrete logarithm. These problems are difficult to solve on classical computers, but quantum computers can effectively crack these encryption algorithms in polynomial time through Shor's algorithm, making the secure storage of data unguaranteed;

[0005] 2. Traditional protection is usually designed for specific application scenarios and lacks flexibility. For example, RSA performs well in key exchange but performs poorly in emerging applications such as homomorphic encryption.

[0006] Based on this, the present invention proposes a data security protection method and system, which relies on solving the shortest vector problem (SVP) on a lattice. It is quite difficult in both classical and quantum computing environments and can support a variety of cryptographic applications. This flexibility enables the security protection method to adapt to different application requirements and ensure the secure storage of data. Summary of the invention

[0007] The purpose of the present invention is to provide a data security protection method and system to solve the deficiencies in the background technology.

[0008] In order to achieve the above object, the present invention provides the following technical solution: a data security protection method, the protection method comprising the following steps:

[0009] The protection system obtains the data set information and the corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, and obtains an adjustment coefficient by combining the storage difference index and the importance index;

[0010] The adjustment coefficient is input into the parameter generator, and the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter. The random matrix and secret key vector are obtained according to the dimension parameter and modulus parameter. The public key vector is calculated by the random matrix, secret key vector and noise. After the data to be encrypted is converted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypted by the ciphertext.

[0011] When the user needs to read the data, after receiving the ciphertext, the key vector is used to decrypt and recover the data.

[0012] In a preferred embodiment, the adjustment coefficient is obtained by combining the storage difference index and the importance index, including the following steps:

[0013] The storage difference index and the importance index are combined to obtain the adjustment coefficient, which is expressed as:

[0014] In the formula, tz x is the adjustment coefficient, Z storage is the storage difference index, Z data is the importance index, α and β are the proportional coefficients of the storage difference index and the importance index respectively, and both α and β are greater than 0.

[0015] In a preferred embodiment, the adjustment coefficient is input into a parameter generator, and the parameter generator automatically outputs a dimension parameter, a modulus parameter, and a noise parameter, including the following steps:

[0016] Input the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter and modulus parameter. The expression is: Where n new represents the adjusted dimension parameter, q new Indicates the adjusted modulus parameter, n old represents the dimension parameter before adjustment, q old Indicates the modulus parameter before adjustment, tz x is the adjustment factor;

[0017] Then, the noise parameter range is generated based on the adjusted dimension parameter and the adjusted modulus parameter: [-μ·q new ~μ·q new ],in, μ represents the adjustment amplitude, and the noise parameters are randomly generated within the noise parameter range.

[0018] In a preferred embodiment, a random matrix and a secret key vector are obtained according to a dimension parameter and a modulus parameter, and a public key vector is obtained by calculating the random matrix, the secret key vector and noise, including the following steps:

[0019] Generates a random matrix of size n based on the dimension parameter new ×n new , generate a secret key vector of size n new , the public key vector is calculated based on the random matrix, secret key vector and noise, and the expression is: P = A × s + e, where P is the public key vector, A is the random matrix, s is the secret key vector, and e is the noise parameter.

[0020] In a preferred embodiment, encrypting the data in the storage medium by ciphertext comprises the following steps:

[0021] Convert the dataset into a binary vector and generate a random vector based on the dimension parameter Size is n new , calculate the ciphertext, the function expression is:

[0022] , where c1 and c2 are ciphertexts, m is the binary vector of the original data, r is a random vector, A is a random matrix, P is the public key vector, and A T represents the transposed matrix of the random matrix A, q new is the modulus.

[0023] In a preferred embodiment, after receiving the ciphertext, decryption and data recovery are performed using the key vector, including the following steps:

[0024] The user uses the secret key vector to decrypt the ciphertext and recover the data, and calculates the binary vector of the decrypted data, which is expressed as: In the formula, m * is the binary vector of the decrypted data, c1 and c2 are the ciphertext, s is the secret key vector, and q new is the modulus, c1 T represents the transpose of the ciphertext vector c1;

[0025] Get the binary vector m of the decrypted data * After that, if the binary vector m of the decrypted data * If it is equal to the binary vector m of the original data, the decryption is successful.

[0026] In a preferred embodiment, the logic for obtaining the storage difference index is as follows: obtaining the remaining capacity of the storage medium, the remaining capacity is obtained by subtracting the used capacity from the total capacity, then obtaining the data volume of the data set, subtracting the data volume from the remaining capacity to obtain the storage margin, obtaining the read and write speed and redundancy of the storage medium based on the system log, normalizing the storage margin, the read and write speed, and the redundancy so that the value ranges of the storage margin, the read and write speed, and the redundancy are mapped to [0, 1], obtaining the normalized value of the storage margin, the normalized value of the read and write speed, and the normalized value of the redundancy, and adding the normalized value of the storage margin to the normalized value of the read and write speed and the redundancy to obtain the storage difference index;

[0027] The logic for obtaining the importance index is: obtaining the usage frequency and access frequency of the data set, and summing the usage frequency and access frequency to obtain the importance index.

[0028] A data security protection system includes a calculation module, a vector output module, and an encryption module;

[0029] Calculation module: obtains the data set information and corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, and obtains an adjustment coefficient by combining the storage difference index and the importance index;

[0030] Vector output module: input the adjustment coefficient into the parameter generator, the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter, obtains the random matrix and secret key vector according to the dimension parameter and modulus parameter, and obtains the public key vector through the random matrix, secret key vector and noise calculation;

[0031] Encryption module: After converting the data to be encrypted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypting the ciphertext.

[0032] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0033] 1. The present invention automatically outputs dimension parameters, modulus parameters and noise parameters through a parameter generator, obtains a random matrix and a secret key vector according to the dimension parameters and the modulus parameters, obtains a public key vector through the random matrix, the secret key vector and the noise calculation, converts the data to be encrypted into a binary vector, calculates the ciphertext in combination with the public key vector and the binary vector, encrypts the data in the storage medium through the ciphertext, and when the user needs to read the data, after receiving the ciphertext, decrypts and recovers the data through the secret key vector. The protection system relies on solving the shortest vector problem (SVP) on the lattice, which is quite difficult in both classical and quantum computing environments, and can support a variety of cryptographic applications. This flexibility enables the security protection method to adapt to different application requirements and ensure the safe storage of data.

[0034] 2. The present invention obtains the data set information and the corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, obtains the adjustment coefficient by combining the storage difference index and the importance index, and inputs the adjustment coefficient into a parameter generator. The parameter generator automatically outputs the dimensionality parameter, the modulus parameter and the noise parameter, so that the generated public parameters are more suitable for the current data set and the storage medium environment, thereby improving the security of data storage and ensuring the storage efficiency of the storage medium. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0036] Figure 1 The present invention is a flow chart of the method. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] Example 1: Please refer to Figure 1 As shown, a data security protection method described in this embodiment includes the following steps:

[0039] The protection system obtains the data set information and corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, obtains the adjustment coefficient by combining the storage difference index and the importance index, inputs the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter, obtains the random matrix and secret key vector according to the dimension parameter and modulus parameter, obtains the public key vector by the random matrix, secret key vector and noise calculation, converts the data to be encrypted into a binary vector, calculates the ciphertext by combining the public key vector and the binary vector, encrypts the data in the storage medium by the ciphertext, and when the user needs to read the data, after receiving the ciphertext, decrypts and recovers the data by the secret key vector.

[0040] Dynamically generate encryption parameters based on importance index and storage difference index: By calculating the importance index and storage difference index of the data set, the system can generate a suitable adjustment coefficient and dynamically adjust the encryption parameters (such as dimension parameter, modulus parameter and noise parameter) based on the coefficient. This enables the encryption scheme to be adaptively adjusted according to the importance of the data and the characteristics of the storage medium, ensuring that different types of data can receive the most appropriate protection and preventing security vulnerabilities or resource waste caused by a one-size-fits-all encryption strategy.

[0041] Enhanced data security protection capabilities: By selecting appropriate dimensions and modulus parameters, especially for data with a high importance index, the system can significantly improve the security of data encryption and prevent attackers from cracking ciphertexts through conventional means. At the same time, the introduction of noise parameters further increases the ambiguity of ciphertexts and enhances the ability to resist side channel attacks and statistical analysis attacks.

[0042] Optimize encryption based on storage media characteristics: Before encrypting data, the system will analyze the storage media's read and write speed, storage margin, and redundancy, measure the storage media's characteristics through the storage difference index, and adjust encryption parameters accordingly. This ensures that storage resources are fully utilized without sacrificing security, and avoids performance degradation or resource waste caused by excessive encryption.

[0043] Reduce storage and computational overhead: By optimizing encryption parameters, the system is able to reduce the size of keys and ciphertexts, thereby reducing storage requirements. At the same time, appropriate selection of noise parameters ensures a balance between computational complexity and security, reduces computational overhead during decryption, and improves the efficiency of data reading and writing.

[0044] Accurate data recovery: Through appropriate parameter settings, the system can effectively reduce errors during decryption and ensure the integrity and accuracy of the data. Especially in high-noise conditions, the impact of noise on data recovery can be effectively offset through a carefully designed decryption process.

[0045] Improve system robustness: The system can automatically adjust encryption strength and strategy when processing data of different importance. This adaptability improves the robustness and flexibility of the system when facing various threats and attack scenarios.

[0046] Diverse application scenarios: This solution can be applied to different application scenarios, from personal data protection to enterprise-level data security, and can provide flexible encryption solutions. Whether it is important data stored on high-performance storage media or a large amount of data that needs to be preserved for a long time, the encryption strength and resource allocation can be adjusted according to actual needs.

[0047] Meeting compliance requirements: By dynamically adjusting encryption parameters, the system can more easily meet compliance requirements in different regions and industries, such as GDPR or HIPAA. This flexibility makes the encryption solution widely applicable around the world.

[0048] Comprehensive data protection: Encryption parameters generated by combining the storage difference index and importance index ensure the maximum security of different data in different storage environments and reduce the risk of data leakage.

[0049] Enhanced data management and monitoring capabilities: The system can adjust encryption policies in real time according to the importance of data and the characteristics of storage media, which not only improves data security, but also enhances data management and monitoring capabilities, allowing managers to deploy and adjust data security policies more effectively.

[0050] This application automatically outputs dimension parameters, modulus parameters and noise parameters through a parameter generator, obtains a random matrix and a secret key vector according to the dimension parameters and the modulus parameters, obtains a public key vector through the random matrix, the secret key vector and the noise calculation, converts the data to be encrypted into a binary vector, calculates the ciphertext in combination with the public key vector and the binary vector, encrypts the data in the storage medium through the ciphertext, and when the user needs to read the data, after receiving the ciphertext, decrypts and recovers the data through the secret key vector. The protection system relies on solving the shortest vector problem (SVP) on the lattice, which is quite difficult in both classical and quantum computing environments, and can support a variety of cryptographic applications. This flexibility enables the security protection method to adapt to different application requirements and ensure the secure storage of data.

[0051] The present application obtains the data set information and the corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, obtains the adjustment coefficient by combining the storage difference index and the importance index, and inputs the adjustment coefficient into a parameter generator. The parameter generator automatically outputs the dimension parameter, the modulus parameter and the noise parameter, so that the generated public parameters are more suitable for the current data set and the storage medium environment, thereby improving the security of data storage and ensuring the storage efficiency of the storage medium.

[0052] Embodiment 2: A protection system obtains data set information and corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, and calculates a data set importance index based on the data set information, including the following steps:

[0053] Get the dataset information, including the dataset name, size, data type, data structure, data source, etc.

[0054] Obtain storage media information, including storage media type (such as hard disk, SSD, cloud storage, etc.), storage location (local or remote), storage capacity, read and write speed, etc.;

[0055] The logic for obtaining the storage difference index is as follows: obtain the remaining capacity of the storage medium, which is obtained by subtracting the used capacity from the total capacity, then obtain the data volume of the data set, subtract the data volume from the remaining capacity to obtain the storage margin, obtain the read and write speed and redundancy of the storage medium based on the system log, normalize the storage margin, read and write speed, and redundancy, map the value range of the storage margin, read and write speed, and redundancy to [0,1], obtain the normalized value of the storage margin, the normalized value of the read and write speed, and the normalized value of the redundancy, add the normalized value of the storage margin to the normalized value of the read and write speed, and then add the redundancy to obtain the storage difference index. The smaller the storage difference index is, the worse the overall performance of the storage medium is, and the storage medium does not support larger dimension parameters and modulus parameters.

[0056] The corresponding relationship between dimension parameter, modulus parameter and storage margin is as follows:

[0057] Dimension (n): A larger dimension usually means greater security and computational complexity, but it also increases the storage requirements for data. A larger n may reduce the storage margin because the storage occupancy of data such as keys and ciphertexts will increase;

[0058] Modulus (q): A larger modulus q will increase the size of the key and ciphertext, which in turn consumes more storage space. Therefore, a larger value of q may reduce the storage margin.

[0059] The corresponding relationship between dimension parameters, modulus parameters and read and write speeds is as follows:

[0060] Dimension (n): A larger dimension usually increases the amount of computation, resulting in more frequent read and write operations. If the storage medium has a slow read and write speed, this may become a performance bottleneck. Therefore, when choosing a larger n, it is recommended to choose a storage medium with a higher read and write speed.

[0061] Modulus (q): A larger modulus will increase the size of the ciphertext and key, resulting in an increase in the amount of data that needs to be transmitted and stored, which may reduce the read and write efficiency. Therefore, when the modulus is large, a storage medium with a higher read and write speed should also be selected.

[0062] The corresponding relationship between dimension parameter, modulus parameter and redundancy is as follows:

[0063] Dimension (n): In data encryption, a larger dimension can enhance security, but it also leads to an increase in the amount of data. To ensure data security, a storage medium with higher redundancy can be used;

[0064] Modulus (q): A larger modulus will also increase the size of the data, so when using a larger modulus, you can also consider increasing the redundancy of the storage medium to ensure data integrity and security.

[0065] To sum up, the smaller the storage margin, the more it is necessary to reduce the dimension parameter and modulus parameter values; the smaller the read and write speed, the more it is necessary to reduce the dimension parameter and modulus parameter values; the smaller the redundancy, the more it is necessary to reduce the dimension parameter and modulus parameter values.

[0066] The logic for obtaining the importance index is: obtain the usage frequency and access frequency of the data set, and then sum the usage frequency and access frequency to obtain the importance index. The smaller the importance index is, the less frequently the data set is accessed and used in the enterprise, and the less important it is to the enterprise. It does not require larger dimension parameters or modulus parameters.

[0067] The greater the importance index of a data set, the higher the value or sensitivity of the data set in the system. In this case, choosing a larger dimension and modulus helps enhance data security. The following is an explanation of the reasons:

[0068] The greater the importance index of a data set, the more critical and sensitive the data set is in the business or application scenario. In order to ensure its security, a larger dimension and modulus are usually required. The dimension n and modulus q directly affect the security and anti-attack capability of the encryption system. The following are the specific reasons:

[0069] Enhanced encryption complexity: The dimension n represents the dimension of the lattice. The higher the lattice dimension, the more difficult it is for an attacker to crack the system. High dimensions increase the size of the key space, making brute force cracking and other attack methods more difficult. Therefore, for data sets with a large importance index, in order to prevent potential attacks, it is usually necessary to select a larger dimension to enhance the complexity of encryption.

[0070] Improved anti-attack capability: Larger dimensions mean more complex mathematical structures, which makes it difficult for some known attack methods (such as the closest vector problem (SVP) and the shortest vector problem (CVP)) to achieve effective attacks in high-dimensional grids, which is especially important for protecting sensitive data.

[0071] Increase the security of ciphertext: The modulus q controls the range of integers used in the encryption process. A larger modulus q will make the ciphertext more ambiguous (that is, the same plaintext is more likely to correspond to different ciphertexts), thereby improving the security of the encryption scheme. For data sets with a large importance index, using a larger q can prevent attackers from inferring the plaintext by analyzing the relationship between ciphertexts.

[0072] Effectiveness in resisting attacks: A large modulus q will expose attackers to more possibilities when attempting reverse calculations, increasing the difficulty of cracking ciphertexts, which is particularly critical for protecting highly sensitive and important data sets.

[0073] Combining the storage difference index and the importance index to obtain the adjustment coefficient includes the following steps:

[0074] The storage difference index and the importance index are combined to obtain the adjustment coefficient, which is expressed as:

[0075] In the formula, tz x is the adjustment coefficient, Z storage is the storage difference index, Z data is the importance index, α and β are the proportional coefficients of the storage difference index and the importance index respectively, and both α and β are greater than 0.

[0076] The larger the storage difference index and the importance index are, the larger the dimensional parameters and modulus parameter values ​​initially generated by the protection system are. In this application, the larger the adjustment coefficient is, the smaller the storage difference index and the importance index are, and the more it is necessary to reduce the dimensional parameters and modulus parameter values ​​initially generated.

[0077] Input the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter, modulus parameter, and noise parameter, including the following steps:

[0078] In this application, the security protection of data is involved, therefore, the initial preset dimension parameters and modulus parameters select the largest dimension parameters and modulus parameters (that is, set under the premise that the storage medium performance is optimal and the data set is the most important);

[0079] Input the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter and modulus parameter. The expression is:

[0080] Where n new represents the adjusted dimension parameter, q new Indicates the adjusted modulus parameter, n old represents the dimension parameter before adjustment, q old Indicates the modulus parameter before adjustment, tz x is the adjustment factor;

[0081] Then, the noise parameter range is generated based on the adjusted dimension parameter and the adjusted modulus parameter: [-μ·q new ~μ·q new ],in, μ represents the adjustment amplitude, and the noise parameters are randomly generated within the noise parameter range.

[0082] The random matrix and secret key vector are obtained according to the dimension parameter and modulus parameter, and the public key vector is obtained by the random matrix, secret key vector and noise calculation, including the following steps:

[0083] Generates a random matrix of size n based on the dimension parameter new ×n new, generate a secret key vector of size n new , the public key vector is calculated based on the random matrix, secret key vector and noise, and the expression is: P = A × s + e, where P is the public key vector, A is the random matrix, s is the secret key vector, and e is the noise parameter.

[0084] After the original data to be encrypted is converted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypted by the ciphertext, including the following steps:

[0085] Convert the dataset into a binary vector and generate a random vector based on the dimension parameter Size is n new , calculate the ciphertext, the function expression is:

[0086] , where c1 and c2 are ciphertexts, m is the binary vector of the original data, r is a random vector, A is a random matrix, P is the public key vector, and A T represents the transposed matrix of the random matrix A, q new is the modulus.

[0087] When the user needs to read the data, after receiving the ciphertext, the key vector is used to decrypt and recover the data, including the following steps:

[0088] The user uses the secret key vector to decrypt the ciphertext and recover the data, and calculates the binary vector of the decrypted data, which is expressed as: In the formula, m * is the binary vector of the decrypted data, c1 and c2 are the ciphertext, s is the secret key vector, and q new is the modulus, c1 T Represents the transpose of the ciphertext vector c1. Since c1 is a column vector, its transpose is a row vector, which can be multiplied by the secret key vector after transposition.

[0089] Get the binary vector m of the decrypted data * After that, if the binary vector m of the decrypted data * If it is equal to the binary vector m of the original data, the decryption is successful.

[0090] In order to better illustrate the technical solution of Example 2, this application gives the following examples:

[0091] Assume that the generated public parameters are as follows:

[0092] Modulus parameter: q new =24;

[0093] Dimension parameter: n new =2.

[0094] Step 1: Generate public key vector and secret key vector:

[0095] Random Matrix:

[0096] Key vector:

[0097] Noise parameters:

[0098] Then the public key vector is:

[0099] Step 2: Data Encryption:

[0100] The original data is 1, then the binary vector of the original data is:

[0101] Random vector:

[0102] Calculate the ciphertext:

[0103] Step 2: Data Decryption:

[0104] Binary vector of decrypted data: Indicates that the original data was successfully restored.

[0105] Embodiment 3: A data security protection system described in this embodiment includes a calculation module, a vector output module, and an encryption module;

[0106] Calculation module: obtains the data set information and corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, obtains the adjustment coefficient by combining the storage difference index and the importance index, and sends the adjustment coefficient to the vector output module;

[0107] Vector output module: input the adjustment coefficient into the parameter generator, the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter, obtains the random matrix and secret key vector according to the dimension parameter and modulus parameter, and obtains the public key vector through the random matrix, secret key vector and noise calculation, and sends the public key vector to the encryption module;

[0108] Encryption module: After converting the data to be encrypted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypting the ciphertext.

[0109] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0110] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0111] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0112] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the above-described system, device and unit can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0113] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A data security protection method, characterized in that: The protection method comprises the following steps: The protection system obtains the data set information and the corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, and obtains an adjustment coefficient by combining the storage difference index and the importance index; The adjustment coefficient is input into the parameter generator, and the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter. The random matrix and secret key vector are obtained according to the dimension parameter and modulus parameter. The public key vector is calculated by the random matrix, secret key vector and noise. After the data to be encrypted is converted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypted by the ciphertext. When the user needs to read the data, after receiving the ciphertext, the key vector is used to decrypt and recover the data.

2. A data security protection method according to claim 1, characterized in that: Combining the storage difference index and the importance index to obtain the adjustment coefficient includes the following steps: The storage difference index and the importance index are combined to obtain the adjustment coefficient, which is expressed as: In the formula, tz x is the adjustment coefficient, Z storage is the storage difference index, Z data is the importance index, α and β are the proportional coefficients of the storage difference index and the importance index respectively, and both α and β are greater than 0.

3. A data security protection method according to claim 2, characterized in that: Input the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter, modulus parameter, and noise parameter, including the following steps: Input the adjustment coefficient into the parameter generator, and the parameter generator automatically outputs the dimension parameter and modulus parameter. The expression is: Where n new represents the adjusted dimension parameter, q new Represents the adjusted modulus parameter, n old represents the dimension parameter before adjustment, q old Indicates the modulus parameter before adjustment, tz x is the adjustment factor; Then, the noise parameter range is generated based on the adjusted dimension parameter and the adjusted modulus parameter: [-μ·q new ~μ·q new ],in, μ represents the adjustment amplitude, and the noise parameters are randomly generated within the noise parameter range.

4. A data security protection method according to claim 3, characterized in that: The random matrix and secret key vector are obtained according to the dimension parameter and modulus parameter, and the public key vector is obtained by the random matrix, secret key vector and noise calculation, including the following steps: Generates a random matrix of size n based on the dimension parameter new ×n new , generate a secret key vector of size n new , the public key vector is calculated based on the random matrix, secret key vector and noise, and the expression is: P = A × s + e, where P is the public key vector, A is the random matrix, s is the secret key vector, and e is the noise parameter.

5. A data security protection method according to claim 4, characterized in that: Encrypting the data in the storage medium through ciphertext includes the following steps: Convert the dataset into a binary vector and generate a random vector based on the dimension parameter The size is n new , calculate the ciphertext, the function expression is: In the formula, c1 and c2 are ciphertexts, m is the binary vector of the original data, r is a random vector, A is a random matrix, P is the public key vector, and A T represents the transposed matrix of the random matrix A, q new is the modulus.

6. A data security protection method according to claim 5, characterized in that: After receiving the ciphertext, decryption and data recovery are performed using the secret key vector, including the following steps: The user uses the secret key vector to decrypt the ciphertext and recover the data, and calculates the binary vector of the decrypted data, which is expressed as: In the formula, m * is the binary vector of the decrypted data, c1 and c2 are the ciphertext, s is the secret key vector, and q new is the modulus, c1 T represents the transpose of the ciphertext vector c1; Get the binary vector m of the decrypted data * After that, if the binary vector m of the decrypted data * If it is equal to the binary vector m of the original data, the decryption is successful.

7. A data security protection method according to claim 6, characterized in that: The logic for obtaining the storage difference index is as follows: obtaining the remaining capacity of the storage medium, the remaining capacity is obtained by subtracting the used capacity from the total capacity, then obtaining the data volume of the data set, subtracting the data volume from the remaining capacity to obtain the storage margin, obtaining the read / write speed and redundancy of the storage medium based on the system log, normalizing the storage margin, the read / write speed and the redundancy so that the value ranges of the storage margin, the read / write speed and the redundancy are mapped to [0, 1], obtaining the normalized value of the storage margin, the normalized value of the read / write speed and the normalized value of the redundancy, adding the normalized value of the storage margin to the normalized value of the read / write speed and adding the redundancy to obtain the storage difference index; The logic for obtaining the importance index is: obtaining the usage frequency and access frequency of the data set, and summing the usage frequency and access frequency to obtain the importance index.

8. A data security protection system, used to implement the protection method according to any one of claims 1 to 7, characterized in that: Including calculation module, vector output module and encryption module; Calculation module: obtains the data set information and corresponding storage medium information that need to be securely protected, generates a storage difference index based on the data set information and the corresponding storage medium information, calculates the importance index of the data set based on the data set information, and obtains an adjustment coefficient by combining the storage difference index and the importance index; Vector output module: input the adjustment coefficient into the parameter generator, the parameter generator automatically outputs the dimension parameter, modulus parameter and noise parameter, obtains the random matrix and secret key vector according to the dimension parameter and modulus parameter, and obtains the public key vector through the random matrix, secret key vector and noise calculation; Encryption module: After converting the data to be encrypted into a binary vector, the ciphertext is calculated by combining the public key vector and the binary vector, and the data in the storage medium is encrypting the ciphertext.

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