Affiliation:
1. Department of Artificial Intelligence and Machine Learning, Symbiosis Centre for Applied Artificial Intelligence (SCAAI), Symbiosis Institute of Technology, Symbiosis International (Deemed) University (SIU), Lavale, Pune 412115, India
2. Department of Computer Engineering, Pimpri Chinchwad College of Engineering, SPPU, Pune 411044, India
Abstract
Biometrics has been evolving as an exciting yet challenging area in the last decade. Though face recognition is one of the most promising biometrics techniques, it is vulnerable to spoofing threats. Many researchers focus on face liveness detection to protect biometric authentication systems from spoofing attacks with printed photos, video replays, etc. As a result, it is critical to investigate the current research concerning face liveness detection, to address whether recent advancements can give solutions to mitigate the rising challenges. This research performed a systematic review using the PRISMA approach by exploring the most relevant electronic databases. The article selection process follows preset inclusion and exclusion criteria. The conceptual analysis examines the data retrieved from the selected papers. To the author, this is one of the foremost systematic literature reviews dedicated to face-liveness detection that evaluates existing academic material published in the last decade. The research discusses face spoofing attacks, various feature extraction strategies, and Artificial Intelligence approaches in face liveness detection. Artificial intelligence-based methods, including Machine Learning and Deep Learning algorithms used for face liveness detection, have been discussed in the research. New research areas such as Explainable Artificial Intelligence, Federated Learning, Transfer learning, and Meta-Learning in face liveness detection, are also considered. A list of datasets, evaluation metrics, challenges, and future directions are discussed. Despite the recent and substantial achievements in this field, the challenges make the research in face liveness detection fascinating.
Subject
Artificial Intelligence,Computer Science Applications,Information Systems,Management Information Systems
Reference153 articles.
1. Sébastien, M.S., Nixon, J.F., and Marcel, N.E. (2019). Handbook of Biometric Anti-Spoofing, Springer. [2nd ed.].
2. Reliable Biometric Authentication with Privacy Protection;Sharma;Adv. Commun. Devices Netw.,2023
3. (2022, December 08). Biometrics Recognition Using Deep Learning: A Survey. Available online: https://doi.org/10.1007/s10462-022-10237-x.
4. Ross, A., and Jain, A.K. (2015). Encyclopedia of Biometrics, Springer.
5. Završnik, A., and Simončič, K. (2023). Artificial Intelligence, Social Harms and Human Rights, Springer International Publishing.
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