Recent advances in biometrie security: A case study of liveness detection in face recognition
Koichi Ito, Takehisa Okano, Takafumi Aoki · 2017
Biometrics using biological or behavioral features to authenticate a person has attracted much attention as a new authentication approach against traditional ones such as key, password, etc. Biometrics technologies provide us better security and greater convenience than traditional person authentication technologies such as key, password and card. Biometric systems with cameras involve the risk of spoofing. For example in face recognition systems, when a malicious person turns a printed face photo of an authenticated user to a camera, a face recognition system may accept the malicious person as the authenticated user. To address the above problem, liveness detection is important to develop secure biometric recognition systems. This paper presents a liveness detection method using deep learning for face recognition systems.