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As Facial Recognition System(FRS) is widely applied in areas such as accesscontrol and mobile payments due to its convenience and high accuracy. Thesecurity of facial recognition is also highly regarded. The Face anti-spoofingsystem(FAS) for face recognition is an important component used to enhance thesecurity of face recognition systems. Traditional FAS used images containingidentity information to detect spoofing traces, however there is a risk ofprivacy leakage during the transmission and storage of these images. Besides,the encryption and decryption of these privacy-sensitive data takes too longcompared to inference time by FAS model. To address the above issues, wepropose a face anti-spoofing algorithm based on facial skin patches leveragingpure facial skin patch images as input, which contain no privacy information,no encryption or decryption is needed for these images. We conduct experimentson several public datasets, the results prove that our algorithm hasdemonstrated superiority in both accuracy and speed.

Enhancing Mobile Privacy and Security: A Face Skin Patch-Based Anti-Spoofing Approach