DP-FedTabDiff wraps an existing federated tabular diffusion model with per-client DP-SGD and reports how the privacy budget, number of clients, and local update count affect synthetic data quality and empirical privacy risk.
Model Inversion Attacks that Exploit Confidence Information and Basic Countermeasures,
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Federated Diffusion Modeling with Differential Privacy for Tabular Data Synthesis
DP-FedTabDiff wraps an existing federated tabular diffusion model with per-client DP-SGD and reports how the privacy budget, number of clients, and local update count affect synthetic data quality and empirical privacy risk.