Query-Efficient Black-Box Membership Inference Attacks via Adaptive Sparse Perturbations
Membership inference attacks (MIAs) determine whether a queried record was included in a model's training set, posing a significant privacy risk to deployed machine learning services. Existing black-box attacks often depend on confidence vectors or numerous augmented queries, resulting in high query costs. This paper i...