Attack of Mechanical Replicas: Liveness Detection With Eye Movements
Attack of Mechanical Replicas: Liveness Detection With Eye Movements
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DOI：
10.1109/tifs.2015.2405345
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发表时间：
2015-04-01
影响因子：
6.8
通讯作者：
Holland, Corey D.
中科院分区：
文献类型：
--
作者：
Komogortsev, Oleg V.;Karpov, Alexey;Holland, Corey D.
本文主要研究眼动生物识别领域的动态检测技术。我们研究了一个特定的场景，在这个场景中，一个冒名顶替者构建了一个人眼的人造复制品。考虑了两种攻击场景：1)冒名顶替者无法访问代表真实用户的生物特征模板，而是利用相关文献中的平均解剖值；2)冒名顶替者可以访问完整的生物特征数据库，并且能够为每个个体使用精确的解剖值。在本文中，基于人类视觉系统的不同方面，对几种现有的眼动生物识别形式在特征和匹配分数水平上进行了活体检测。每种技术区分现场录音和人工录音的能力是通过其相应的虚假欺骗接受率、虚假现场拒绝率和分类率来衡量的。结果表明，当在特征水平上进行活动检测时，眼动生物识别技术对人为记录的规避具有很强的抵抗力。不幸的是，并不是所有的技术都提供适合特征级别的活体检测的特征向量。在匹配分数水平上，活体检测的准确性高度依赖于所采用的生物识别技术。
This paper investigates liveness detection techniques in the area of eye movement biometrics. We investigate a specific scenario, in which an impostor constructs an artificial replica of the human eye. Two attack scenarios are considered: 1) the impostor does not have access to the biometric templates representing authentic users, and instead utilizes average anatomical values from the relevant literature and 2) the impostor gains access to the complete biometric database, and is able to employ exact anatomical values for each individual. In this paper, liveness detection is performed at the feature and match score levels for several existing forms of eye movement biometric, based on different aspects of the human visual system. The ability of each technique to differentiate between live and artificial recordings is measured by its corresponding false spoof acceptance rate, false live rejection rate, and classification rate. The results suggest that eye movement biometrics are highly resistant to circumvention by artificial recordings when liveness detection is performed at the feature level. Unfortunately, not all techniques provide feature vectors that are suitable for liveness detection at the feature level. At the match score level, the accuracy of liveness detection depends highly on the biometric techniques employed.