Protecting DCT Templates for a Face Verification System by Means of Pseudo-random Permutations

Authors:
Marco Grassi;Marcos Faundez-Zanuy
Affiliations:
Department of Biomedical, Electronic and Telecommunication Engineering, Università Politecnica delle Marche, Ancona, Italy;Escola Universitària Politècnica de Mataró (Adscrita a la UPC), MATARO (BARCELONA), Spain 08303
Venue:
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Year:
2009

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Abstract

Biometric template security and privacy are a great concern of biometric systems, because unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. In this paper we present a protection scheme for an identity verification system through biometrical face recognition based on a user dependent pseudo-random ordering of the DCT template coefficients and MPL and RBF Neural Networks for classification. In addition to privacy enhancement, because a hacker can hardly match a fake biometric sample without knowing the pseudo-random ordering this scheme, it also increases the biometric recognition performance.