SIAN: Secure Iris Authentication using Noise

Biometric noise is often discarded in many biometric template protection systems. However, the noise ratio between two templates encodes specific correlational properties that template protection schemes can exploit. Biometric authentication usually occurs between mutually distrusting parties, which calls for privacy-preserving techniques. In this paper, we propose a novel biometric authentication protocol, SIAN(Secure Iris Authentication using Noise), adapting secure two-party computation and incorporating uncertainty constraints from biometric noise for security. We evaluate it on three iris datasets: MMU v1, Ubiris v1, and IITD v1, and observe a low EER degradation. The proposed protocol has information-theoretic security and low computational complexity, making it suitable for practical real-time applications.