Hidden Facial Verification Scheme in IoT Cloud Environment Based on Homomorphic Privacy Information Retrieval

With the popularization of face recognition technology in IoT-Cloud, the problem of privacy leakage caused by it is becoming more and more serious. Although traditional privacy protection schemes can improve security to a certain extent, there is still a risk of data leakage when facing semi-trusted cloud servers. To this end, this paper proposes an anonymized face verification scheme for IoT convergence scenarios, which achieves real-time retrieval and secure matching of dense face features in virtual device copies by combining homomorphic encryption (CKKS) and privacy information retrieval (PIR) for anonymized face verification. The scheme ensures that the semi-trusted cloud server cannot obtain user-specific index information and matching results. Experiments show that the scheme’s verification accuracy in the ciphertext state on the LFW dataset is consistent with the plaintext, up to 97.06%, and can complete a privacy-protected anonymized facial verification process within seconds. The scheme is feasible in security demanding scenarios.