Random Distance Method for Generating Unimodal and Multimodal Cancelable Biometric Features

Abstract

The cancelable biometric-based template protection method proposed in this paper addresses security and privacy concerns emerging from the phenomenal usage of biometric systems. Cancelable biometric transforms the original biometric identity of a user to a pseudo-biometric identity that is used for storage and matching purposes. The use of pseudo-identity mitigates privacy risks and allows revocability in case of compromise. This paper proposes a novel template transformation technique named random distance method which not only generates discriminative and privacy preserving revocable pseudo-biometric identities, but also reduces their size by 50%. Extensive experimentation is performed to analyze recognition and protection performance on unimodal and multimodal pseudo-identities generated with various biometric modalities such as face, thermal face, palmprint, palmvein, and fingervein. It is observed that the matching performance obtained with the proposed cancelable templates in the worst-case is closer to the performance achieved in the original domain. Also, multimodal cancelable biometric templates generated with the proposed method are observed for improved performance. Furthermore, the proposed approach is successfully analyzed for non-invertibilty, unlinkability, as well as its resistance for various types of attacks like attacks via record multiplicity, dictionary, false accepts, and brute force.