A new framework evaluates privacy metrics for synthetic tabular data by inserting controlled risks and testing detection under no-box threat models on public datasets.
The trade-off between information utility and disclosure risk in a ga synthetic data generator.Joint UNECE/Eurostat Work Session on Statistical Data Confidentiality, 2019
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Empirical Evaluation of Structured Synthetic Data Privacy Metrics: Novel experimental framework
A new framework evaluates privacy metrics for synthetic tabular data by inserting controlled risks and testing detection under no-box threat models on public datasets.