A Survey on Iris Presentation Attack Detection

Iris recognition technology has been widely deployed in various real-world scenarios due to its advantages of uniqueness, stability, non-contact nature, accuracy and so on. However, many existing iris recognition systems are still vulnerable to various attacks during the authentication process, posing potential security risks. Among different types of attacks, presentation attacks (PAs) occur in the early stage of iris image acquisition and take various forms. Therefore, iris presentation attack detection (IPAD) has become one of the primary security issues that need to be addressed in iris recognition technology, attracting significant attention from academia and industry. To the best of our knowledge, this is the first Chinese review paper in the field of IPAD, aiming to help researchers quickly and comprehensively understand the relevant knowledge and development trends in this field. Overall, this paper provides a comprehensive summary of IPAD, covering broad topics on the challenges, terminology, PA types, mainstream methods, publicly available datasets, competitions, interpretability and so on. Specifically, we first introduce the background of IPAD, existing security vulnerabilities in iris recognition systems, and the objectives of PAs. Then, IPAD methods are categorized into two groups: Hardware-based and software-based methods, by considering the use of additional hardware devices. Further categorization and analysis are provided for software-based methods based on feature extraction manners. Additionally, we collate open-source methods, publicly available datasets, and summarize past relevant competitions. Finally, we discuss the future development direction of IPAD for further research.