MUSE embeds a watermark in tabular synthetic data by selecting, among several generated candidate rows, the one with the highest keyed hash score, enabling detection without model inversion.
Generating synthetic data in finance: opportunities, challenges and pitfalls
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MUSE: Model-Agnostic Tabular Watermarking via Multi-Sample Selection
MUSE embeds a watermark in tabular synthetic data by selecting, among several generated candidate rows, the one with the highest keyed hash score, enabling detection without model inversion.