Benchmarking Deepfake Attacks on Deep Face Recognition Systems

Summary

The authors introduce a taxonomy and benchmarking framework that classifies deepfake attacks by intent and generative mechanism, then evaluate them against deep face recognition systems. Diverse deepfake attacks commonly exceed 70% success and, in some regimes, surpass 90%. The study finds that attack success depends on the degree of identity controllability rather than visual quality.

Topics

• Deepfakes and impersonation

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