A new shadow-model hyperparameter selection method (KL-LiRA) makes membership inference attacks nearly as effective without knowing target hyperparameters, and training-data-based hyperparameter tuning shows no detectable extra MIA leak under DP.
Membership Inference Attacks Against Machine Learning Models,
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Hyperparameters in Score-Based Membership Inference Attacks
A new shadow-model hyperparameter selection method (KL-LiRA) makes membership inference attacks nearly as effective without knowing target hyperparameters, and training-data-based hyperparameter tuning shows no detectable extra MIA leak under DP.