Encrypted Similarity Calculation via Homomorphic Encryption
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Solution Overview
Problem
Authentication systems using additive homomorphic encryption face challenges in preventing information leakage and spoofing attacks, particularly in maintaining the secrecy of original data during operations between apparatuses.
Innovation Solution
A similarity degree calculation apparatus that processes and compares encrypted data using a temporary key, ensuring that the similarity degree calculation remains encrypted throughout the process, thereby preventing information leakage and enabling secure authentication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If additive homomorphic encryption is used to perform arithmetic operations on encrypted data, then the ability to calculate similarity degrees on encrypted data is improved, but the risk of information leakage and spoofing attacks increases
Solution Approach 1:
The patent introduces a trusted third party (server) that holds the secret key and performs decryption operations. This intermediary enables the system to benefit from homomorphic encryption's computational capabilities while mitigating security risks by centralizing secret key management and preventing direct exposure of encrypted data between client devices
Solution Approach 2:
The system divides the encryption key into two parts: a public key held by client devices for encryption, and a secret key held by the server for decryption. This segmentation allows encrypted data to be processed and compared while maintaining security through separated key management responsibilities
2Reliability
If encrypted data is transmitted and processed between apparatuses, then data secrecy is improved, but the complexity of the authentication system increases
Solution Approach 1:
Client devices perform self-encryption of data using the public key before transmission, and the server performs self-decryption using the secret key. This self-service approach to encryption/decryption simplifies the overall system architecture by eliminating the need for complex key exchange protocols and mutual authentication mechanisms
3Reliability
If homomorphic encryption is used to protect original data secrecy, then security against spoofing attacks is improved, but the operational efficiency and speed of similarity calculation deteriorates
Solution Approach 1:
The system performs partial decryption by the server (decrypting only the encrypted data received from clients, not all data in the system) and then transfers the decrypted data to client devices for final similarity calculation. This partial action approach balances security requirements with computational efficiency by limiting the server's processing burden while maintaining data protection
Data Source
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AI summary
Based on an encrypted feature vector C (comparison ciphertext) encrypted with a public key pk of a decryption apparatus and an encrypted feature vector C' (target ciphertext) encrypted with the public key pk of the decryption apparatus, and a random number (temporary key) generated by a random number generation unit 303 (temporary key generation unit), an encrypted random similarity degree calculation unit 314 (interim similarity degree ciphertext calculation unit) performs calculation for calculationg a similarity degree in a first stage, with two encrypted feature vectors C and C' kept encrypted, thereby calculating a second challenge C". The decryption apparatus decrypts the second challenge C^ with a secret key sk of the decryption apparatus, and performs calculation for calculating the similarity degree in a second stage with a result of the decryption kept encrypted with the temporary key, thereby calculating a second response Z. A plaintext similarity degree extraction unit 315 (similarity degree calculation unit) decrypts the second response Z with the temporary key, thereby calculating a similarity degree d.