Evaluation of multimodal biometric score fusion rules under spoof attacks
Zahid Akhtar, Giorgio Fumera, Gian Luca Marcialis, Fabio Roli · 2012
Recent works have shown that multimodal biometric sys-tems can be evaded by spoofing only a single biometric trait. In this paper, we propose a method to evaluate the robust-ness of such systems against spoofing attacks, when score-level fusion rules are used. The aim is to rank several score-level fusion rules, to allow the designer to choose the most robust one according to the model predictions. Our method does not require to fabricate fake biometric traits, and al-lows one to simulate different possible spoofing attacks us-ing the information of genuine and impostor distributions. Reported results, using data set containing realistic spoof-ing attacks, show that our method can rank correctly score-level fusion rules under spoofing attacks. 1.