A Survey on Physical Adversarial Attacks against Face Recognition Systems

TL;DR

This survey comprehensively reviews physical adversarial attacks on face recognition systems, categorizing methods, analyzing challenges, and discussing defenses to guide future research in this critical security area.

Contribution

It provides the first systematic overview of physical adversarial attack methods on face recognition, categorizes them, and discusses defense strategies and future directions.

Findings

Physical attacks pose severe security threats to face recognition systems.

Categorization of attack methods based on physical mediums.

Discussion of current defense strategies and future research directions.

Abstract

As Face Recognition (FR) technology becomes increasingly prevalent in finance, the military, public safety, and everyday life, security concerns have grown substantially. Physical adversarial attacks targeting FR systems in real-world settings have attracted considerable research interest due to their practicality and the severe threats they pose. However, a systematic overview focused on physical adversarial attacks against FR systems is still lacking, hindering an in-depth exploration of the challenges and future directions in this field. In this paper, we bridge this gap by comprehensively collecting and analyzing physical adversarial attack methods targeting FR systems. Specifically, we first investigate the key challenges of physical attacks on FR systems. We then categorize existing physical attacks into three categories based on the physical medium used and summarize how the research in each category has evolved to address these challenges. Furthermore, we review current defense strategies and discuss potential future research directions. Our goal is to provide a fresh, comprehensive, and deep understanding of physical adversarial attacks against FR systems, thereby inspiring relevant research in this area.