CamPro: Camera-based Anti-Facial Recognition
Wenjun Zhu
Network and Distributed System Security (NDSS) Symposium 2024 · Day 3 · Physical Attacks
The rapid advancement and pervasive deployment of deep learning-based facial recognition (FR) systems have introduced significant privacy concerns, ranging from unauthorized surveillance to potential cybercrime. While FR offers undeniable conveniences, its potential for abuse has sparked widespread debate, leading to lawsuits and even outright bans in various jurisdictions. Existing anti-facial recognition (AFR) solutions primarily operate as post-processing methods, modifying images *after* they have been captured by a camera module. This approach, however, presents a critical vulnerability: an adversary with direct access to the camera module or a compromised operating system can intercept raw, unprotected images, thereby bypassing all privacy safeguards.