Generating provably secure cancelable fingerprint templates based on correlation-invariant random filtering

Abstract

Biometric authentication has attracted attention because of its high security and convenience. However, biometric feature such as fingerprint can not be revoked like passwords. Thus once the biometric data of a user stored in the system has been compromised, it can not be used for authentication securely for his/her whole life long. To address this issue, an authentication scheme called cancelable biometrics has been studied. However, there remains a major challenge to achieve both strong security and practical accuracy. In this paper, we propose new methods for generating cancelable fingerprint templates with provable security based on the well-known chip matching algorithm for fingerprint verification and correlation-invariant random filtering for transforming templates. Experimental evaluation shows that our methods can be applied to fingerprint authentication without much loss in accuracy compared with the conventional chip matching algorithm.