2023/08/09 by Qiushi Guo, Guo, Qiushi
Computer Science · #Access control #Artificial intelligence #Biometric Identification and Security #Computer Vision and Pattern Recognition (cs.CV) #Computer science #Computer security #Computer vision #Encryption #FOS: Computer and information sciences #Face (sociological concept) #Face recognition and analysis #Facial recognition system #Pattern recognition (psychology) #Spoofing attack
paper · pdf · doi:10.48550/arxiv.2308.04798
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2023/08/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
As Facial Recognition System(FRS) is widely applied in areas such as access control and mobile payments due to its convenience and high accuracy. The security of facial recognition is also highly regarded. The Face anti-spoofing system(FAS) for face recognition is an important component used to enhance the security of face recognition systems. Traditional FAS used images containing identity information to detect spoofing traces, however there is a risk of privacy leakage during the transmission and storage of these images. Besides, the encryption and decryption of these privacy-sensitive data takes too long compared to inference time by FAS model. To address the above issues, we propose a face anti-spoofing algorithm based on facial skin patches leveraging pure facial skin patch images as input, which contain no privacy information, no encryption or decryption is needed for these images. We conduct experiments on several public datasets, the results prove that our algorithm has demonstrated superiority in both accuracy and speed.