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