Multi-Biometric Fuzzy Vault based on Face and Fingerprints
Christian Rathgeb, Benjamin Tams, Johannes Merkle, Vanessa Nesterowicz, Ulrike Korte, Matthias Neu · 2023
The fuzzy vault scheme has been established as cryptographic primitive suitable for privacy-preserving biometric authentication. To improve accuracy and privacy protection, biometric information of multiple characteristics can be fused at feature level prior to locking it in a fuzzy vault. In this work, we provide a formalisation of feature-level fusion in multi-biometric fuzzy vaults, on the basis of which relevant security issues are elaborated. In a case study, we construct a multi-biometric fuzzy vault based on face and multiple fingerprints. On a multi-biometric database constructed from the FRGCv2 face and the MCYT-100 fingerprint databases, a perfect recognition accuracy is achieved at a false accept security above 30 bits. We define countermeasures for observed security issues, that are commonly ignored and may impair the overall system’s security. Finally, a method for extending the fuzzy vault scheme with a password is proposed.