Improving Robustness to Model Inversion Attacks via Mutual Information Regularization

11 Sep 2020Tianhao WangYuheng ZhangRuoxi Jia

This paper studies defense mechanisms against model inversion (MI) attacks -- a type of privacy attacks aimed at inferring information about the training data distribution given the access to a target machine learning model. Existing defense mechanisms rely on model-specific heuristics or noise injection... (read more)

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