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Dynamic facial presentation attack detection for automated border control systems

机译:用于自动边界控制系统的动态面部表情攻击检测

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Millions of passengers travel every day, border crossing being one of their most common activities. At these points it is extremely important that security is completely guaranteed. However, the maintaining adequate security levels is a very demanding issue. This has promoted the development of systems capable of providing support to border authorities by automatising some of their tasks. Thus, Automated Border Control (ABC) systems have become a key tool. These systems increase the flow of travellers as they can achieve fast evaluations of individuals through their machine-readable travel documents. However, this has motivated the appearance of attacks that try to avoid the identity detection of individuals by these systems. Presentation Attack Detection (PAD) algorithms have emerged to mitigate such a problem. This paper presents the On-the-Fly Presentation Attack Detection (FlyPAD) framework that implements a set of dynamic PAD techniques. It allows multiple types of attacks to be detected as the traveller approaches the ABC system, rather than being static in front of the cameras. Several experiments have been carried out, both in the laboratory and in real environments, obtaining promising results.
机译:每天都有数百万的旅客旅行,过境是他们最常见的活动之一。在这些时候,完全保证安全性是非常重要的。但是,保持足够的安全级别是一个非常苛刻的问题。这促进了能够通过自动执行某些任务来向边境当局提供支持的系统的开发。因此,自动边界控制(ABC)系统已成为关键工具。这些系统增加了旅行者的流量,因为他们可以通过其机读旅行证件快速评估个人。但是,这激发了攻击的出现,这些攻击试图避免通过这些系统来检测个人的身份。演示攻击检测(PAD)算法已经出现,可以缓解此类问题。本文介绍了实时演示攻击检测(FlyPAD)框架,该框架实现了一组动态PAD技术。当旅行者接近ABC系统时,它可以检测多种类型的攻击,而不是在摄像机前静止不动。在实验室和实际环境中都进行了几次实验,获得了可喜的结果。

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