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Does Differentially Private Synthetic Data Lead to Synthetic Discoveries?
March 21, 2024, 4:41 a.m. | Ileana Montoya Perez, Parisa Movahedi, Valtteri Nieminen, Antti Airola, Tapio Pahikkala
cs.LG updates on arXiv.org arxiv.org
Abstract: Background: Synthetic data has been proposed as a solution for sharing anonymized versions of sensitive biomedical datasets. Ideally, synthetic data should preserve the structure and statistical properties of the original data, while protecting the privacy of the individual subjects. Differential privacy (DP) is currently considered the gold standard approach for balancing this trade-off.
Objectives: The aim of this study is to evaluate the Mann-Whitney U test on DP-synthetic biomedical data in terms of Type I …
abstract arxiv biomedical cs.lg data datasets differential differential privacy discoveries privacy solution statistical stat.ml synthetic synthetic data type versions
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