Feasibility of Privacy Preserving Minutiae-Based Fingerprint Matching

While biometric data, such as fingerprints, are increasingly used for identification and authentication, their inability to be revoked once compromised raises privacy concerns. To mitigate these concerns, in this ongoing research, we explore the use of Multiparty Computation (MPC), which allows secure computations on encrypted data, as an option for privacy-preserving fingerprint matching. Despite MPC’s known drawback of slowing down computation, recent advancements make it a viable option for real-world applications. Our research focuses on implementing and optimizing a minutiae-based fingerprint matching algorithm with MPC, addressing the challenge of maintaining privacy while ensuring reasonable computation times. We present our implementation using SourceAFIS optimized for MPC and evaluate its performance to assess if current protocols are ready for deployment in time critical scenarios. Preliminary results show promise, emphasizing our ongoing research to achieve a fully-fledged MPC implementation with high accuracy.