Anis Trabelsi
ABSTRACT
The progress made in deep learning has allowed the deployment of more powerful biometric authentication systems instead of traditional ones based on passwords or PIN codes. Facial recognition is widely used on smartphones to grant user access. However, advances in deep learning also improve methods for doctoring images and videos. A fraudulent user can use these methods to steal the identity of another person. It is very easy for impostors to present to the smartphone an image or video of the victim's face displayed on another screen. In this paper, we describe the security risks when a facial recognition system is attacked by presenting an image, a video or an interactive deepfake displayed on a screen. We also present a deep learning-based method to detect this kind of attack.
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Index Terms
- Recapture Detection to Fight Deep Identity Theft
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