AI RESEARCH
ID-Eraser: Proactive Defense Against Face Swapping via Identity Perturbation
arXiv CS.CV
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ArXi:2604.21465v1 Announce Type: new Deepfake technologies have rapidly advanced with modern generative AI, and face swapping in particular poses serious threats to privacy and digital security. Existing proactive defenses mostly rely on pixel-level perturbations, which are ineffective against contemporary swapping models that extract robust high-level identity embeddings. We propose ID-Eraser, a feature-space proactive defense that removes identifiable facial information to prevent malicious face swapping.