Dealing with Subject Similarity in Differential Morphing Attack Detection

arXiv:2404.07667v1 Announce Type: cross
Abstract: The advent of morphing attacks has posed significant security concerns for automated Face Recognition systems, raising the pressing need for robust and effective Morphing Attack Detection (MAD) methods able to effectively address this issue. In this paper, we focus on Differential MAD (D-MAD), where a trusted live capture, usually representing the criminal, is compared with the document image to classify it as morphed or bona fide. We show these approaches based on identity features are …

address arxiv attack attacks automated cs.cr cs.cv detection effectively face recognition focus issue recognition security security concerns similarity systems