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Purpose of the research: In the biometric community, visible humancharacteristics are popular and viable for verification and identification onmobile devices. However, imposters are able to spoof such characteristics bycreating fake and artificial biometrics to fool the system. Visible biometricsystems have suffered a high-security risk of presentation attack. Methods: Inthe meantime, challenge-based methods, in particular, gaze tracking and pupildynamic appear to be more secure methods than others for contactless biometricsystems. We review the existing work that explores gaze tracking and pupildynamic liveness detection. The principal results: This research analyzesvarious aspects of gaze tracking and pupil dynamic presentation attacks, suchas state-of-the-art liveness detection algorithms, various kinds of artifacts,the accessibility of public databases, and a summary of standardization in thisarea. In addition, we discuss future work and the open challenges to creating asecure liveness detection based on challenge-based systems.

Presentation Attack Detection Methods based on Gaze Tracking and Pupil Dynamic: A Comprehensive Survey