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

Reported by arXiv cs.CR (Calister Nnona)

Summary by Cyber Security News5 Nov 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2611.06342

arXiv:2611.06342v1 Announce Type: new Abstract: The records that could train the most useful models, such as a hospital's patient files, are often the ones an institution cannot share. We propose CoRTeC, a method that releases synthetic versions of such records under differential privacy. Differential privacy places a proven limit on what the synthetic data can reveal about any person, and in particular on membership inference.

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