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Biometric Identification and Presentation-Attack Detection using Micro- and Macro-Movements of the Eyes

机译:使用眼睛微观和宏观运动的生物识别和呈现 - 攻击检测

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We study involuntary micro-movements of both eyes, in addition to saccadic macro-movements, as biometric characteristic. We develop a deep convolutional neural network that processes binocular oculomotoric signals and identifies the viewer. In order to be able to detect presentation attacks, we develop a model in which the movements are a response to a controlled stimulus. The model detects replay attacks by processing both the controlled but randomized stimulus and the ocular response to this stimulus. We acquire eye movement data from 150 participants, with 4 sessions per participant. We observe that the model detects replay attacks reliably; compared to prior work, the model attains substantially lower error rates.
机译:除了扫视宏观运动之外,我们还研究了两只眼睛的非自愿微观运动,作为生物特征。我们开发一个深卷积神经网络,处理双目血管磁性信号并识别观众。为了能够检测呈现攻击,我们开发了一种模型,其中运动是对受控刺激的响应。该模型通过处理受控但随机刺激和对该刺激的眼睛响应来检测重放攻击。我们从150名参与者获得眼球运动数据,每个参与者有4个会议。我们观察到模型可靠地检测重播攻击;与事先工作相比,该模型达到了更低的误差率。

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