Generative AI models for face image synthesis (StyleGAN, Diffusion) can
now create high resolution photo-realistic face images. Face recognition
(FR) is exposed to a new threat as synthetic faces can be used as
deepfakes to perform Presentation Attacks (PAs) or Injection Attacks
(IAs). Injection Attack Detection (IAD) of deepfakes is currently a
topic of investigation. Presentation Attack Detection (PAD) is mostly
focusing on print or display, of faces from real data subjects, as
Presentation Attack Instruments (PAIs), but is not yet considering
synthetic faces. This proposal aims to study the impact of synthetic
face images from generative AI models on PAD (mobile phone scenario)
measuring the accuracy of current PAD when exposed to synthetic faces
and compare this accuracy to IAD. Several generative models will be
considered in this study.