Secure Computation for Privacy Preserving Biometric Data Retrieval and Authentication

The goal of this research is to develop provable secure computation techniques for two biometric security tasks; namely biometric data retrieval and authentication. We first present models for privacy and security that delineate the conditions under which biometric data disclosure are allowed, the conditions under which the protocol for data exchange should be provable secure, and the conditions under which the computation should be provable private. We then present a novel technique based on singular value decomposition and homomorphic encryption to achieve secure computation for biometric data retrieval. Finally we show a proof-of-concept implementation of the proposed techniques to realize a privacy preserving speaker verification system.