AdvDiffusion: Adversarial Patches Generation for Face Recognition With High Transferability in Physical Domain

Summary

The paper presents AdvDiffusion, a method for generating adversarial face patches that can be pasted onto a face to cause face recognition models to make false identity judgments. It first selects a patch region using facial gradient maps, then adds noise to an image and denoises it with a pre-trained diffusion model, guided by an adversarial loss. Experiments report effective attacks on black-box face recognition models in both digital and physical settings, with better robustness to complex physical environments than some state-of-the-art methods.

Topics

• Adversarial machine learning

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