Attack Vectors for Face Recognition Systems: A Comprehensive Review

Abstract

Face Recognition Systems (FRS) are critical and essential components for user authentication via biometrics. To name a few, baking, e-Commerce, and border control are entities propelling their progress. These are of immense importance due to their economic and social relevance. FRS widespread usage leads to security vulnerabilities that need to be identified and mitigated. This article provides a comprehensive review of potential attacks on recently discovered vulnerabilities from 2017–2024. Our work is significant regarding FRS development because their impact in terms of security. The novelty is a systematic review to properly categorize threat vectors and their severity toward FRS over the past eight years. We categorize, summarize, and analyze the threat vectors toward FRS to this end. We also elaborate on the threat taxonomy for existing Architecture Reference Architecture (ARA) to identify threats on user-based authentication FRS. Our findings show the most persistent attack vectors, usage trends, severity, functionality, and level of sophistication required to perform them. We present a comprehensive description of each to create more resilient and trustable systems for this fast-growing technology. This article can be used by researchers and practitioners interested in the state-of-the-art FRS attack vectors to develop more secure systems.