AIBearisharXiv – CS AI · 8h ago7/10
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On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics
Researchers demonstrate significant privacy vulnerabilities in tabular diffusion models (TDMs), which are increasingly used to generate synthetic data as privacy-preserving alternatives. Through membership inference attacks in both black-box and white-box settings, the study reveals that attackers can successfully breach these systems without perfect knowledge of training data or massive computational resources, while also exposing flaws in commonly-used privacy metrics.