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