Privacy-preserving Cosine Similarity Computation with Malicious Security Applied to Biometric Authentication

ePrint Report: Privacy-preserving Cosine Similarity Computation with Malicious Security Applied to Biometric Authentication

Nan Cheng, Melek Önen, Aikaterini Mitrokotsa, Oubaïda Chouchane, Massimiliano Todisco, Alberto Ibarrondo

Computing $\Delta(\mathbfit{x},\mathbfit{y}) \geq \tau$, the distance between two vectors $\mathbfit{x}$ and $\mathbfit{y}$ chained with a comparison to a predefined public threshold $\tau$, is an essential functionality that is extensively used in privacy-sensitive applications such as biometric authentication and identification, machine learning algorithms ({\em e.g.,} linear regression, k-nearest neighbors etc.) or typo-tolerant password-based authentication. Cosine similarity …

authentication biometric computation computing delta eprint report malicious privacy public report security similarity threshold