Praguna Manvi
ABSTRACT
Biometric signal consisting of irrelevant or non-distinctive features can contain useful correlational properties that privacy-preserving verification schemes can exploit. While an efficient protocol for iris verification using noise has been presented [33], it is not applicable to other widely used modalities, i.e., face and fingerprint, since the methods of noise extraction and comparison are different. In this work, we design a verification protocol for secure dot product computation and also propose noise extraction mechanisms for face and fingerprint modalities. We evaluate the performance of the protocol on CFP, LFW, CelebA, FVC 2004 DB1A, DB2A, DB3A, and SOCOFing datasets. While the protocol exhibits a slight degradation in accuracy, it provides information-theoretic security with a practical computational complexity.
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Index Terms
- S-BAN: Secure Biometric Authentication using Noise
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