OSLO: One-Shot Label-Only Membership Inference Attacks

Neural Information Processing Systems 

We introduce One-Shot Label-Only (OSLO) membership inference attacks (MIAs), which accurately infer a given sample's membership in a target model's training set with high precision using just a single query, where the target model only returns the predicted hard label. This is in contrast to state-of-the-art label-only attacks which require 6000 queries, yet get attack precisions lower than OSLO's.