CoRTeC: A Differentially Private Release for Synthetic Tabular Data, Decodable by Any Generator

Summary

CoRTeC releases synthetic tabular data under differential privacy by spending the privacy budget once on a small file of noisy counts, which anyone can decode into synthetic rows at no further privacy cost. A maximum-entropy decoder works without a language model, and at epsilon = 2 it trains classifiers to within 0.02 AUC of a real sample of the same size on the Adult dataset. The strongest membership attack stays far below the bound the budget allows.

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