Fang Meiling, Damer Naser, Kirchbuchner Florian, Kuijper Arjan
Fraunhofer Institute for Computer Graphics Research IGD, Darmstadt, Germany.
Mathematical and Applied Visual Computing, TU Darmstadt, Darmstadt, Germany.
Pattern Recognit. 2022 Mar;123:108398. doi: 10.1016/j.patcog.2021.108398. Epub 2021 Oct 26.
Face masks have become one of the main methods for reducing the transmission of COVID-19. This makes face recognition (FR) a challenging task because masks hide several discriminative features of faces. Moreover, face presentation attack detection (PAD) is crucial to ensure the security of FR systems. In contrast to the growing number of masked FR studies, the impact of face masked attacks on PAD has not been explored. Therefore, we present novel attacks with real face masks placed on presentations and attacks with subjects wearing masks to reflect the current real-world situation. Furthermore, this study investigates the effect of masked attacks on PAD performance by using seven state-of-the-art PAD algorithms under different experimental settings. We also evaluate the vulnerability of FR systems to masked attacks. The experiments show that real masked attacks pose a serious threat to the operation and security of FR systems.
口罩已成为减少新冠病毒传播的主要方法之一。这使得人脸识别（FR）成为一项具有挑战性的任务，因为口罩会掩盖面部的几个判别特征。此外，人脸呈现攻击检测（PAD）对于确保FR系统的安全性至关重要。与越来越多的蒙面FR研究相比，面部蒙面攻击对PAD的影响尚未得到探索。因此，我们提出了在演示中放置真实口罩的新型攻击以及受试者戴口罩的攻击，以反映当前的现实世界情况。此外，本研究通过在不同实验设置下使用七种最先进的PAD算法，研究了蒙面攻击对PAD性能的影响。我们还评估了FR系统对蒙面攻击的脆弱性。实验表明，真实的蒙面攻击对FR系统的运行和安全构成了严重威胁。
