2018/10/08 by Meng Shen, Zichen Liao, Shen, Meng +10
Computer Science · #Biometric Identification and Security #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Face recognition and analysis #User Authentication and Security Systems #cs.CR
paper · pdf · doi:10.48550/arxiv.1810.03323
arxiv created 2018/10/08 · openalex publication_date 2018/10/08 · arxiv updated 2018/10/09 · openalex created_date 2018/10/12 · openalex updated_date 2026/07/28
Face liveness detection has become a widely used technique with a growing importance in various authentication scenarios to withstand spoofing attacks. Existing methods that perform liveness detection generally focus on designing intelligent classifiers or customized hardware to differentiate between the image or video samples of a real legitimate user and the imitated ones. Although effective, they can be resource-consuming and detection results may be sensitive to environmental changes. In this paper, we take iris movement as a significant liveness sign and propose a simple and efficient liveness detection system named IriTrack. Users are required to move their eyes along with a randomly generated poly-line, and trajectories of irises are then used as evidences for liveness detection. IriTrack allows checking liveness by using data collected during user-device interactions. We implemented a prototype and conducted extensive experiments to evaluate the performance of the proposed system. The results show that IriTrack can fend against spoofing attacks with a moderate and adjustable time overhead.