Impostures of Talking Face Systems Using Automatic Face Animation

We present in this paper a new forgery scenario for the evaluation of talking-face verification systems. The scenario is a replay-attack where we assume that the forger has got access to a still picture of the genuine user. The forger is then using a dedicated software to realistically animate the face image, reproducing head and lip movements according to a given speech waveform. The resulting forged video sequence is finally replayed to the sensor. Such attacks are nowadays quite easy to realize for potential forgers and can be opportunities to attempt to forge text-prompted challenge-response configurations of the verification system. We report the evaluation of such forgeries on the BioSecure BMEC talking face database where a set of 430 users are forged according to this face animation procedure. As expected, results show that these forgeries generate much more false acceptation in comparison to the classically used random forgeries. These results clearly show that such kind of forgery attack potentially represents a critical security breach for talking-face verification systems.