Iris Presentation Attack Detection

Iris presentation attack detection (PAD) aims to secure iris recognition systems by identifying fraudulent attempts to spoof the system using artificial eyes, contact lenses, or printed images. Current research heavily utilizes deep convolutional neural networks (CNNs), often incorporating techniques like attention mechanisms and local binary pattern analysis, to differentiate genuine irises from spoofs. A significant focus is on improving generalization across different datasets and attack types, including those unseen during training, and exploring the use of synthetic data to address privacy concerns. The development of robust and generalized PAD methods is crucial for ensuring the reliability and security of iris-based authentication systems in various applications.