SoK: Privacy Attacks on Machine Learning via Explainable AI
Machine learning explanations reveal model behavior beyond predictions, creating attack surfaces for model confidentiality and data privacy. We systematize 25 studies that exploit explanations for model extraction, membership inference, and model inversion, treating attribute inference as partial inversion. Existing wo...
A. Oksuz, Anisa Halimi, Erman Ayday
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