Multi-Biometric Fuzzy Vault based on Face and Fingerprints
This work addresses security and privacy issues in biometric systems for authentication applications, though it appears incremental by extending existing fuzzy vault schemes with multi-biometric fusion.
The authors tackled the problem of improving accuracy and privacy in biometric authentication by constructing a multi-biometric fuzzy vault that fuses face and fingerprint features, achieving perfect recognition accuracy with a false accept security above 30 bits on a combined database.
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. 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. Further, we provide a formalisation of feature-level fusion in multi-biometric fuzzy vaults, on the basis of which relevant security issues are elaborated. Said security issues, for which we define countermeasures, are commonly ignored and may impair the overall system's security.