On the security evaluation of a multibiometric system based on a voting strategy involving likelihood ratio statistic tests

Abstract

Multimodal biometric systems integrate information from multiple sources to improve the performance of a typical unimodal biometric system. The use of multimodal biometric systems has been encouraged by the threat of spoofing, where an impostor fakes a biometric trait. The reason lies on the assumption that, an impostor must fake all the fused modalities to be accepted. Recent studies showed that, there is a vulnerability of the existing fusion schemes in presence of attacks where only a subset of the fused modalities is spoofed. Among the possible information fusion approaches, recently, a framework for the optimal combination of match scores that is based on the likelihood ratio (LR) test has been presented. It is based on the modeling of the distributions of genuine and impostor match scores as a finite Gaussian mixture models. Since standard LR test demonstrated to be very sensitive to spoofing attacks, in this paper we analyze the robustness of a voting strategy based on likelihood ratio test in the presence of spoofing. The analysis has been carried out on the Biosecure multimodal database, demonstrating the advantages of a voting strategy with respect to the standard LR approach.