AI RESEARCH
ReMIA: a Powerful and Efficient Alternative to Membership Inference Attacks against Synthetic Data Generators
arXiv CS.LG
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ArXi:2605.14686v1 Announce Type: new Tabular data sharing under privacy constraints is increasingly important for research and collaboration. Synthetic data generators (SDGs) are a promising solution, but synthetic data remains vulnerable to attacks, such as membership inference attacks (MIAs), which aim to determine whether a specific record was part of the