Robustness of multimodal biometric fusion methods against spoof attacks

Authors:
Ricardo N. Rodrigues;Lee Luan Ling;Venu Govindaraju
Affiliations:
University at Buffalo, Center for Unified Biometrics and Sensors, 216C Southlake Vlg., Buffalo, NY 14261, USA;State University of Campinas (Unicamp), Communications Department, Campinas SP, Brazil;University at Buffalo, Center for Unified Biometrics and Sensors, 216C Southlake Vlg., Buffalo, NY 14261, USA
Venue:
Journal of Visual Languages and Computing
Year:
2009

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Abstract

In this paper, we address the security of multimodal biometric systems when one of the modes is successfully spoofed. We propose two novel fusion schemes that can increase the security of multimodal biometric systems. The first is an extension of the likelihood ratio based fusion scheme and the other uses fuzzy logic. Besides the matching score and sample quality score, our proposed fusion schemes also take into account the intrinsic security of each biometric system being fused. Experimental results have shown that the proposed methods are more robust against spoof attacks when compared with traditional fusion methods.