From Pixels to Reality: Physical-Digital Patch Attacks on Real-World Camera
This work exposes critical vulnerabilities in pervasive vision and sensor-driven authentication infrastructures, posing a security threat to users and systems relying on camera-based authentication.
The paper tackles the problem of camera-based authentication systems by introducing Digital-Physical Adversarial Attacks (DiPA), which uses smartphone screens to display adversarial patches, achieving high success rates and improved transferability in black-box conditions.
This demonstration presents Digital-Physical Adversarial Attacks (DiPA), a new class of practical adversarial attacks against pervasive camera-based authentication systems, where an attacker displays an adversarial patch directly on a smartphone screen instead of relying on printed artifacts. This digital-only physical presentation enables rapid deployment, removes the need for total-variation regularization, and improves patch transferability in black-box conditions. DiPA leverages an ensemble of state-of-the-art face-recognition models (ArcFace, MagFace, CosFace) to enhance transfer across unseen commercial systems. Our interactive demo shows a real-time dodging attack against a deployed face-recognition camera, preventing authorized users from being recognized while participants dynamically adjust patch patterns and observe immediate effects on the sensing pipeline. We further demonstrate DiPA's superiority over existing physical attacks in terms of success rate, feature-space distortion, and reductions in detection confidence, highlighting critical vulnerabilities at the intersection of mobile devices, pervasive vision, and sensor-driven authentication infrastructures.