Presentation Attack

Presentation attack detection (PAD) aims to secure biometric systems by identifying fraudulent attempts to impersonate a genuine user using fake biometric data (e.g., printed photos, masks, deepfakes). Current research heavily focuses on improving the generalization of PAD models across diverse attack types and unseen domains, employing techniques like convolutional neural networks (CNNs), vision transformers (ViTs), generative adversarial networks (GANs), and various feature fusion methods. The development of robust and generalizable PAD systems is crucial for ensuring the security and reliability of biometric authentication in various applications, from access control to financial transactions.