Privacy-preserving correlation-based multi-instance iris verification on malicious server using Cheon-Kim-Kim-Song fully homomorphic encryption
Gopi Suresh Arepalli, Pakkiri Boobalan · Journal of Electronic Imaging · 2024
Homomorphic encryption (HE) has emerged as a prominent research focus in the development of privacy-preserving biometric authentication systems, offering advantages over conventional methods such as cancelable biometrics and biometric cryptosystems. However, many existing systems relying on HE assume the integrity of the server, which may not always be guaranteed. In scenarios where the server behaves maliciously, there is a risk of false acceptances or rejections due to arbitrary computation results aimed at conserving computational resources. To mitigate this concern, we introduce a novel approach called privacy-preserving correlation-based multi-instance iris verification on malicious servers using Cheon-Kim-Kim-Song (CKKS) fully HE (PCMIA). PCMIA leverages CKKS HE to preserve the privacy of iris templates and one-bit checksum to check the correctness of the computed result. Moreover, we introduce discriminant correlation analysis (DCA), a feature-level fusion approach that improves the pair-wise correlations and reduces the between-class correlations. Extensive experimentation with benchmark iris databases demonstrates that PCMIA fulfills the requirements of the template protection scheme, as well as instilling trust in the comparator results.