DEEP LEARNING DETECTION OF FACIAL BIOMETRIC PRESENTATION ATTACK
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Published:2022-07-15
Issue:2
Volume:8
Page:01-18
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ISSN:2454-5872
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Container-title:LIFE: International Journal of Health and Life-Sciences
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language:
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Short-container-title:lijhls
Author:
Shibel Ahmed Muthanna, ,Ahmad Sharifah Mumtazah Syed,Musa Luqman Hakim,Yahya Mohammed Nawfal, , ,
Abstract
Face recognition systems have gained increasing importance in today’s society, which applications range from access controls to secure systems to electronic devices such as mobile phones and laptops. However, the security of face recognition systems is currently being threatened by the emergence of spoofing attacks that happens when someone tries to unauthorizedly bypass the biometric system by presenting a photo, 3-dimensional mask, or replay video of a legit user. The video attacks are perhaps one of the most frequent, cheapest, and simplest spoofing techniques to cheat face recognition systems. This research paper focuses on face liveness detection in video attacks, intending to determine if the provided input biometric samples came from a live face or spoof attack by extracting frames from the videos and classifying them by using the Resnet-50 deep learning algorithm. The majority voting mechanism is used as a decision fusion to derive a final verdict. The experiment was conducted on the spoof videos of the Replay-attack dataset. The results demonstrated that the optimal number of frames for video liveness detection is 3 with an accuracy of 96.93 %. This result is encouraging since the low number of frames requires minimal time for processing.
Publisher
Global Research & Development Services
Subject
Pharmacology (medical),Complementary and alternative medicine,Pharmaceutical Science
Reference32 articles.
1. An introduction to biometric recognition;Jain;IEEE Transactions on circuits and systems for video technology,2004
2. https://doi.org/10.1109/TCSVT.2003.818349
3. Bhatia, R. (2013). Biometrics and face recognition techniques. International Journal of Advanced Research in Computer Science and Software Engineering, 3(5), 93-99.
4. A comparative study of biometric technologies with reference to human interface;Tripathi;International Journal of Computer Applications,2011
5. https://doi.org/10.5120/1842-2493
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