Crowdsourcing attacks on biometric systems

We introduce a new approach for attacking and analyzing biometric-based authentication systems, which involves crowdsourcing the search for potential impostors to the system. Our focus is on voice-based authentication, or speaker verification (SV), and we propose a generic method to use crowdsourcing for identifying candidate "mimics" for speakers in a given target population. We then conduct a preliminary analysis of this method with respect to a well-known text-independent SV scheme (the GMM-UBM scheme) using Mechanical Turk as the crowdsourcing platform.