Accessorize to a Crime - Real and Stealthy Attacks on State-Of-The-Art Face Recognition
Explore a conference talk that delves into real and stealthy attacks on state-of-the-art face recognition systems. Learn about the vulnerabilities of machine learning in ubiquitous applications, particularly in face recognition used for surveillance and access control. Discover how adversaries can manipulate inputs to affect outputs in deep neural networks, and examine specific attack methods targeting facial features and eyeglasses. Investigate experiments conducted in digital environments and the challenges of creating physically realizable impersonations. Gain insights into the risks posed by impersonation attacks and their potential extensions. Understand the implications of these findings for the security of face recognition technology.