Biometric Layering with Fingerprints: Template Security and Privacy Through Multi-Biometric Template Fusion

As biometric applications are gaining popularity, there is increased concern over the loss of privacy and potential misuse of biometric data held in central repositories. We present a biometric authentication framework that constructs a multi-biometric template by layering multiple biometrics of a user, such that it is difficult to separate the individual layers. Thus, the framework uses the biometrics of the user to conceal them among one another. The resulting biometric template is also cancelable if the system is implemented with cancelable biometrics, such as voice. We present a realization of this idea combining two or three different fingerprints of the user, using four different methods of template construction. Three of the methods use less and less information of the constituent biometrics, so as to lower the risk of leakage and cross-link rates. Results are evaluated on publicly available Finger Verification Championship (FVC) 2000, 2002 and NIST fingerprint databases. With the FVC databases, we obtain 2.1%, 3.9% and 3.4% Equal Error Rate on average using the three proposed methods, while the state-of-the-art commercial system achieves 1.9%. Furthermore, we show low cross-link rates under 63% under different scenarios, while genuine identification rates are 100%, with such a small gallery of 55 templates.