Litcius/Paper detail

Multi-Biometric Fuzzy Vault based on Face and Fingerprints

Christian Rathgeb, Benjamin Tams, Johannes Merkle, Vanessa Nesterowicz, Ulrike Korte, Matthias Neu

202315 citationsDOI

Abstract

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.

Topics & Concepts

BiometricsComputer sciencePasswordFingerprint (computing)Face (sociological concept)Fuzzy logicFeature (linguistics)Data miningFingerprint recognitionAuthentication (law)CryptographyComputer securityArtificial intelligencePattern recognition (psychology)Facial recognition systemLinguisticsSociologyPhilosophySocial scienceBiometric Identification and SecurityUser Authentication and Security SystemsAdvanced Steganography and Watermarking Techniques