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.
翻译：研究的目的:在生物鉴别学界,可见的人类特征很受欢迎,在移动设备上进行核查和识别是可行的;然而,冒牌人能够通过制造假冒和人工生物鉴别技术来掩盖这些特征,从而愚弄该系统;明显的生物鉴别系统在演示攻击方面遭遇了高度安全的风险;方法:同时,以挑战为基础的方法,特别是目视跟踪和学生动态动态动态方法,似乎比其他方法更安全,用于没有接触的生物鉴别系统;我们审查了探索视视跟踪和学生动态活性探测的现有工作;主要结果:这项研究分析了视觉跟踪和学生动态演示攻击的各个方面,例如最新的生活状态探测算法、各种文物、公共数据库的可访问性以及该领域标准化概况;此外,我们讨论了今后的工作和在基于挑战的系统的基础上建立安全活性探测的公开挑战。
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