Multimodal biometric fusion: A study on vulnerabilities to indirect attacks

Abstract

Fusion of several biometric traits has traditionally been regarded as more secure than unimodal recognition systems. However, recent research works have proven that this is not always the case. In the present article we analyse the performance and robustness of several fusion schemes to indirect attacks. Experiments are carried out on a multimodal system based on face and iris, a user-friendly trait combination, over the publicly available multimodal Biosecure DB. The tested system proves to have a high vulnerability to the attack regardless of the fusion rule considered. However, the experiments prove that not necessarily the best fusion rule in terms of performance is the most robust to the type of attack considered. © Springer-Verlag 2013.