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On Reliability of Membership Inference Vulnerability Evaluation

Jälkö, Joonas et al.
arXiv (All) · Papers
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cryptography-and-securitymachine-learning
Membership inference attacks (MIAs) are popular methods for empirically assessing the leakage of sensitive information in the training data through models or statistics learned from the data. The MI vulnerability is often evaluated through a binary classifier that tries to predict whether a particul
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