Rapid privacy protection biological characteristic authentication method based on lattice password

Abstract

The invention discloses a quick privacy protection biological characteristic authentication method based on a lattice password, the method comprises the steps of system initialization, key generation, user registration, user authentication and server authentication, the lattice password technology is combined with local sensitive hashing (LSH), the anti-quantum characteristic of the lattice password is utilized to guarantee data security, and the security of the system is improved. The comparison range is reduced in combination with the LSH, the authentication efficiency is improved, the problems of high privacy leakage risk, weak quantum attack resistance and low large-scale authentication efficiency in traditional biological feature authentication are solved, and the method is suitable for scenes with high requirements for privacy protection and authentication speed.

Description

Technical Field

[0001] This invention relates to a fast, privacy-preserving biometric authentication method based on lattice cryptography, belonging to the field of information security technology. Background Technology

[0002] In data transaction scenarios, data merchants need to authenticate the identity of users or data users. Common authentication methods include password authentication, biometric authentication, and multi-factor authentication. Among them, biometric authentication has been widely used in fields such as identity authentication, access control, and mobile payment due to its uniqueness and convenience.

[0003] Traditional biometric authentication methods typically require storing users' biometric templates on the server side. However, this storage and authentication method faces significant challenges: 1. Privacy risk: Biometrics are unique and lifelong. Once the original biometric template stored on the server is leaked, it will cause irreversible damage to the user's privacy. Furthermore, due to the development of quantum computing, traditional encryption schemes are unable to resist quantum attacks. 2. Secure transmission issues: During registration or authentication, users need to transmit biometric data to the server. If the transmission link is not adequately protected, the data may be eavesdropped on or tampered with. 3. Recognition efficiency issues: In large-scale databases, the server needs to compare the features to be authenticated with thousands of templates in the database, resulting in huge computational overhead and authentication delays. Summary of the Invention

[0004] The purpose of this invention is to provide a fast, privacy-preserving biometric authentication method based on lattice cryptography, in order to solve the problems of high privacy leakage risk, resistance to quantum attacks, and low efficiency of large-scale database authentication in existing biometric authentication technologies.

[0005] To solve the above-mentioned technical problems, the technical solution of the present invention is as follows: A fast, privacy-preserving biometric authentication method based on lattice cryptography includes the following steps: S1. System Initialization: The Trusted Center generates and publishes common system parameters, including error learning parameters, data parameters, and locality-sensitive hash parameters; S2. Key Generation: A system master private key is generated by the trusted center and securely distributed to all legitimate users; S3. User Registration: Users generate their own biometric template and expand the vector, encrypt the expanded vector with their private key to obtain ciphertext, and calculate the local sensitive hash bucket address of the expanded vector. The ciphertext obtained by encrypting with the private key and the local sensitive hash bucket address are then uploaded to the server. S4. User Authentication: The user collects their current biometric features and expands the vector, then uses their private key to encrypt the expanded vector to generate a token. At the same time, the user calculates the local sensitive hash bucket address of the expanded vector and sends the token obtained by encrypting the expanded vector with their private key and the local sensitive hash bucket address to the server. S5. Server Authentication: Upon receiving the authentication request token and the Local Sensitive Hash Bucket address, the server quickly filters out candidate ciphertexts using the Local Sensitive Hash Bucket address. For each candidate ciphertext and the received token, a discrimination value is calculated. Without decryption, the server determines whether the distance between the biometric template generated during user registration and the current biometrics collected during user authentication is less than a threshold. If one ciphertext is successfully authenticated, the server returns a successful user authentication result; if all ciphertexts fail to authenticate, the server returns a failed user authentication result.

[0006] As a preferred embodiment, in step S1, the error-learning parameters include modulus q, dimensions n, m, common matrix A, and noise distribution χ; the data parameters include feature dimension d, scaling factor τ, and authentication threshold θ; and the locality-sensitive hashing parameters include the number of hash tables L, the number of hash functions k, and the hash function family H.

[0007] As a preferred embodiment, step S3 includes the following steps: (1) The user constructs a registration extension vector x, which contains the original feature x, a constant term for distance calculation, the sum of squares of x, and the square of the threshold θ; (2) The user uses his private key s to encrypt each item of the extended vector x to generate ciphertext Cx; (3) The user uses the hash function family H to calculate the L bucket addresses of the extended vector x and gives the address set Adx; (4) The user uploads the ciphertext Cx and the bucket address Adx to the server.

[0008] As a preferred embodiment, step S4 includes the following steps: (1) The user constructs an authentication extension vector y, which contains twice the features y, the sum of squares of y, and a constant term for distance calculation; (2) The user uses his private key s to encrypt each item of the extended vector y to generate a token Ty; (3) The user uses the hash function family H to calculate the L bucket addresses of vector y and gives the address set Ady; (4) The user sends the ciphertext Ty and the bucket address Ady to the server.

[0009] As a preferred embodiment, step S5 includes the following steps: (1) The server uses the locality-sensitive hash bucket address Ady to quickly locate all possible candidate ciphertexts Cx in the locality-sensitive hash table; (2) For each candidate ciphertext Cx and the received token The server calculates an authentication decision value D; (3) The server determines whether authentication is successful based on the authentication decision value D; (4) If one ciphertext is successfully authenticated, the user authentication is successful. If all candidate ciphertexts fail to be authenticated, the authentication is deemed to have failed.

[0010] Beneficial effects: Compared with existing technologies, this invention is a secure and efficient biometric authentication scheme based on lattice cryptography and locality-sensitive hashing (LSH). This invention combines lattice cryptography with LSH, utilizing the quantum resistance of lattice cryptography to ensure data security, and combining it with LSH to reduce the comparison range and improve authentication efficiency. It solves the problems of high privacy leakage risk, weak resistance to quantum attacks, and low efficiency of large-scale authentication in traditional biometric authentication, and is suitable for scenarios with high requirements for privacy protection and authentication speed. Attached Figure Description

[0011] Figure 1 This is a flowchart of the overall solution of the present invention; Figure 2 This is a schematic diagram of the user registration phase of the present invention; Figure 3 This is a schematic diagram of the user authentication phase of the present invention. Detailed Implementation

[0012] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0013] The solution of this invention involves three parties: a trusted center, a user, and a server. First, the trusted center initializes the system and generates public parameters and keys. At the same time Securely distributed to users. During the user registration phase, a biometric template is generated. And expand the vector, using the key Encryption yields ciphertext Simultaneously calculate Locally Sensitive Hash Bucket Address ,Will and Uploaded to the server, such as Figure 1 As shown. During the user authentication phase, the system collects its own current characteristics. And expand, also using a key Encryption to obtain token ,calculate Locally Sensitive Hash Bucket Address ,Will and Send to the server. The server uses... Quickly filter out candidate ciphertexts And through calculation and Specific inner product between Determine the vector without decryption and The system checks whether the distance is less than a threshold to achieve efficient and privacy-preserving identity authentication.

[0014] The specific implementation is as follows: 1. System initialization phase: Performed by the Trusted Center, setting system security parameters. Learning parameters with errors (including modulus) Dimensions ,matrix Noise distribution ), data vector dimension Estimated range related parameters (upper limit of components) Maximum Sum of Squares ), scaling factor Authentication threshold parameter At the same time, set the relevant parameters for locality-sensitive hashing (number of hash buckets). Each group A hash function, distance to threshold Projection window width and generate Group hash function family Each of them and Output system common parameters .

[0015] 2. Key generation phase: Performed by a trusted center, generating the LWE master private key. and will Distribute securely to legitimate users.

[0016] 3. User registration phase: Performed by the user.

[0017] 3.1 Generate biometric vectors based on individual characteristics .

[0018] 3.2 Constructing the Registration Extension Vector The vector length is .

[0019] 3.3 For the extended vector Each component Encryption: Select a random matrix ,calculate Calculate message encoding From the noise distribution Medium sampling noise ,calculate , Indicates calculation The inner product of the two variables is used to output the registration ciphertext. .

[0020] 3.4 Using a family of hash functions Calculate vector of bucket address .

[0021] 3.5 users will Uploaded to the server. The server then... Will Stored in the corresponding hash bucket.

[0022] 4. User authentication phase: Performed by the user.

[0023] 4.1 Users use real-time acquired biometric vectors .

[0024] 4.2 Constructing the Authentication Extension Vector The vector length is .

[0025] 4.3 For the extended vector Each component Encryption: Select a random matrix ,calculate Calculate message encoding From the noise distribution Medium sampling noise ,calculate , Indicates calculation The inner product of the two tokens outputs the authentication token. .

[0026] 4.4 Using a family of hash functions Calculate vector of Locally Sensitive Hash Bucket Addresses .

[0027] 4.5 users will Send to the server.

[0028] 5. Server authentication phase: Performed by the server.

[0029] 5.1 The server, based on the received... Locate the corresponding locality-sensitive hash bucket from the locality-sensitive hash table and retrieve all candidate registration ciphertexts. .

[0030] 5.2 For each candidate ciphertext and the received token Calculate a discriminant value The calculation method is as follows: .

[0031] 5.3 Based on the discriminant value Make a judgment: 0 If so, the authentication is successful; If not, authentication will fail.

[0032] 5.4 If one encrypted message is successfully authenticated, the system returns a success message for user authentication; if all encrypted messages fail to be authenticated, the system returns a failure message for user authentication.

[0033] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. A fast, privacy-preserving biometric authentication method based on lattice cryptography, characterized in that, Includes the following steps: S1. System Initialization: The Trusted Center generates and publishes common system parameters, including error learning parameters, data parameters, and locality-sensitive hash parameters; S2. Key Generation: A system master private key is generated by the trusted center and securely distributed to all legitimate users; S3. User Registration: Users generate their own biometric template and expand the vector, encrypt the expanded vector with their private key to obtain ciphertext, and calculate the local sensitive hash bucket address of the expanded vector. The ciphertext obtained by encrypting with the private key and the local sensitive hash bucket address are then uploaded to the server. S4. User Authentication: The user collects their current biometric features and expands the vector, then uses their private key to encrypt the expanded vector to generate a token. At the same time, the user calculates the local sensitive hash bucket address of the expanded vector and sends the token obtained by encrypting the expanded vector with their private key and the local sensitive hash bucket address to the server. S5. Server Authentication: Upon receiving the authentication request token and the Local Sensitive Hash Bucket address, the server quickly filters out candidate ciphertexts using the Local Sensitive Hash Bucket address. For each candidate ciphertext and the received token, a discrimination value is calculated. Without decryption, the server determines whether the distance between the biometric template generated during user registration and the current biometrics collected during user authentication is less than a threshold. If one ciphertext is successfully authenticated, the server returns a successful user authentication result; if all ciphertexts fail to authenticate, the server returns a failed user authentication result.

2. The fast privacy-preserving biometric authentication method based on lattice cryptography according to claim 1, characterized in that, In step S1, the error-learning parameters include modulus q, dimensions n, m, common matrix A, and noise distribution χ; the data parameters include feature dimension d, scaling factor τ, and authentication threshold θ; and the locality-sensitive hashing parameters include the number of hash tables L, the number of hash functions k, and the hash function family H.

3. The fast privacy-preserving biometric authentication method based on lattice cryptography according to claim 1, characterized in that, Step S3 includes the following steps: (1) The user constructs a registration extension vector x, which contains the original feature x, a constant term for distance calculation, the sum of squares of x, and the square of the threshold θ; (2) The user uses his private key s to encrypt each item of the extended vector x to generate ciphertext Cx; (3) The user uses the hash function family H to calculate the L bucket addresses of the extended vector x and gives the address set Adx; (4) The user uploads the ciphertext Cx and the bucket address Adx to the server.

4. The fast privacy-preserving biometric authentication method based on lattice cryptography according to claim 1, characterized in that, Step S4 includes the following steps: (1) The user constructs an authentication extension vector y, which contains twice the features y, the sum of squares of y, and a constant term for distance calculation; (2) The user uses his private key s to encrypt each item of the extended vector y to generate a token Ty; (3) The user uses the hash function family H to calculate the L bucket addresses of vector y and gives the address set Ady; (4) The user sends the ciphertext Ty and the bucket address Ady to the server.

5. The fast privacy-preserving biometric authentication method based on lattice cryptography according to claim 1, characterized in that, Step S5 includes the following steps: (1) The server uses the locality-sensitive hash bucket address Ady to quickly locate all possible candidate ciphertexts Cx in the locality-sensitive hash table; (2) For each candidate ciphertext Cx and the received token The server calculates an authentication decision value D; (3) The server determines whether authentication is successful based on the authentication decision value D; (4) If one ciphertext is successfully authenticated, the user authentication is successful. If all candidate ciphertexts fail to be authenticated, the authentication is deemed to have failed.

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