MemGuard: Defending against Black-Box Membership Inference Attacks via Adversarial Examples

23 Sep 2019Jinyuan JiaAhmed SalemMichael BackesYang ZhangNeil Zhenqiang Gong

In a membership inference attack, an attacker aims to infer whether a data sample is in a target classifier's training dataset or not. Specifically, given a black-box access to the target classifier, the attacker trains a binary classifier, which takes a data sample's confidence score vector predicted by the target classifier as an input and predicts the data sample to be a member or non-member of the target classifier's training dataset... (read more)

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