When initially proposed, synthetic data for disclosure control was generally dismissed as
unlikely to be implemented in practice. Thirty years later, synthetic data are becoming a …

Most statistical agencies release randomly selected samples of Census microdata, usually
with sample fractions under 10% and with other forms of statistical disclosure control (SDC) …

There is growing interest in synthetic data generation as a means of allowing access to
useful data whilst preserving confidentiality. In particular, synthetic microdata generation …

The synthpop package for R https://www. synthpop. org. uk provides tools to allow data
custodians to create synthetic versions of confidential microdata that can be distributed with …

Objective This study sought to evaluate whether synthetic data derived from a national
coronavirus disease 2019 (COVID-19) dataset could be used for geospatial and temporal …

This paper proposes and compares measures of identity and attribute disclosure risk for
synthetic data. Data custodians can use the methods proposed here to inform the decision …

The proliferation of deep learning techniques led to a wide range of advanced analytics
applications in important business areas such as predictive maintenance or product …

Recent advances in generative models facilitate the creation of synthetic data to be made
available for research in privacy-sensitive contexts. However, the analysis of synthetic data …