Face authentication systems have gained widespread popularity because of their user-friendly usage and increasing recognition accuracy. Unfortunately, the boom in mobile social networks has bought with it media-based facial forgery; a critical threat where an adversary forges or replays the victim’s photograph/video to fool the system. In this article, we propose EchoFace, an effective and robust liveness detection system to enhance face authentication in defending against media-based attacks, which works with today’s smartphones/smartwatches without any hardware modification. EchoFace uses active acoustic sensing to differentiate the uneven stereostructure of the face and the flat forged media. Our proposed scheme effectively extracts the desired reflection profiles from the target. Moreover, we propose effective similarity measurements of reflection profiles to distinguish live users from forged media, which works robustly under various environmental conditions. EchoFace only requires low cost and universally equipped acoustic sensors without human intervention for liveness detection, which can be easily deployed in a variety of application scenarios. We implement EchoFace on commercial smartphones, and experiment results show that EchoFace achieves an average detection accuracy higher than 96% and false alarm rate lower than 4% across various media attacks and different levels of background noise. This shows its great potential to enhance the security of widely deployed face authentication systems in real scenarios.

中文翻译：

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EchoFace：基于声学传感器的媒体攻击检测，用于面部认证

面部认证系统由于其用户友好的用法和不断提高的识别精度而获得了广泛的普及。不幸的是，移动社交网络的兴旺带动了基于媒体的面部伪造。攻击者伪造或重放受害者的照片/视频以欺骗系统的严重威胁。在本文中，我们提出了EchoFace，这是一种有效而强大的活动检测系统，可增强人脸身份验证以防御基于媒体的攻击，该系统可与当今的智能手机/智能手表配合使用，而无需进行任何硬件修改。EchoFace使用主动声音感应来区分面部和平坦的锻造介质的不均匀立体结构。我们提出的方案有效地从目标中提取了所需的反射轮廓。而且，我们提出了有效的反射剖面相似度测量方法，以将现场用户与伪造媒体区分开来，伪造媒体在各种环境条件下均表现出色。EchoFace仅需要低成本且通用的声学传感器，而无需人工干预即可进行活动检测，可以轻松地将其部署在各种应用场景中。我们在商用智能手机上实现了EchoFace，实验结果表明，在各种媒体攻击和不同水平的背景噪音下，EchoFace的平均检测准确率均高于96％，误报率低于4％。这显示了其在实际场景中增强广泛部署的面部认证系统的安全性的巨大潜力。EchoFace仅需要低成本且通用的声学传感器，而无需人工干预即可进行活动检测，可以轻松地将其部署在各种应用场景中。我们在商用智能手机上实现了EchoFace，实验结果表明，在各种媒体攻击和不同水平的背景噪音下，EchoFace的平均检测准确率均高于96％，误报率低于4％。这显示了其在实际场景中增强广泛部署的面部认证系统的安全性的巨大潜力。EchoFace仅需要低成本且通用的声学传感器，而无需人工干预即可进行活动检测，可以轻松地将其部署在各种应用场景中。我们在商用智能手机上实现了EchoFace，实验结果表明，在各种媒体攻击和不同水平的背景噪音下，EchoFace的平均检测准确率均高于96％，误报率低于4％。这显示了其在实际场景中增强广泛部署的面部认证系统的安全性的巨大潜力。实验结果表明，EchoFace在各种媒体攻击和不同背景噪声水平下的平均检测准确率均高于96％，误报率低于4％。这显示了其在实际场景中增强广泛部署的面部认证系统的安全性的巨大潜力。实验结果表明，EchoFace在各种媒体攻击和不同背景噪声水平下的平均检测准确率均高于96％，误报率低于4％。这显示了其在实际场景中增强广泛部署的面部认证系统的安全性的巨大潜力。