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Advancing microdata privacy protection: A review of synthetic data methods
Synthetic data generation is a powerful tool for privacy protection when considering public
release of record‐level data files. Initially proposed about three decades ago, it has …
release of record‐level data files. Initially proposed about three decades ago, it has …
30 years of synthetic data
J Drechsler, AC Haensch - arxiv preprint arxiv:2304.02107, 2023 - arxiv.org
The idea to generate synthetic data as a tool for broadening access to sensitive microdata
has been proposed for the first time three decades ago. While first applications of the idea …
has been proposed for the first time three decades ago. While first applications of the idea …
30 years of synthetic data
The idea to generate synthetic data as a tool for broadening access to sensitive microdata
has been proposed for the first time three decades ago. While first applications of the idea …
has been proposed for the first time three decades ago. While first applications of the idea …
Advancing Microdata Privacy Protection: A Review of Synthetic Data
J Hu, CMK Bowen - arxiv preprint arxiv:2308.00872, 2023 - arxiv.org
Synthetic data generation is a powerful tool for privacy protection when considering public
release of record-level data files. Initially proposed about three decades ago, it has …
release of record-level data files. Initially proposed about three decades ago, it has …
Deep generative models in DataSHIELD
S Lenz, M Hess, H Binder - BMC medical research methodology, 2021 - Springer
Background The best way to calculate statistics from medical data is to use the data of
individual patients. In some settings, this data is difficult to obtain due to privacy restrictions …
individual patients. In some settings, this data is difficult to obtain due to privacy restrictions …
Synthesizing geocodes to facilitate access to detailed geographical information in large-scale administrative data
We investigate whether generating synthetic data can be a viable strategy for providing
access to detailed geocoding information for external researchers, without compromising the …
access to detailed geocoding information for external researchers, without compromising the …
Generating Poisson-distributed differentially private synthetic data
H Quick - Journal of the Royal Statistical Society Series A …, 2021 - academic.oup.com
The dissemination of synthetic data can be an effective means of making information from
sensitive data publicly available with a reduced risk of disclosure. While mechanisms exist …
sensitive data publicly available with a reduced risk of disclosure. While mechanisms exist …
Risk-efficient Bayesian data synthesis for privacy protection
Statistical agencies utilize models to synthesize respondent-level data for release to the
public for privacy protection. In this study, we efficiently induce privacy protection into any …
public for privacy protection. In this study, we efficiently induce privacy protection into any …
Bayesian data synthesis and disclosure risk quantification: An application to the consumer expenditure surveys
J Hu, TD Savitsky - arxiv preprint arxiv:1809.10074, 2018 - arxiv.org
The release of synthetic data generated from a model estimated on the data helps statistical
agencies disseminate respondent-level data with high utility and privacy protection …
agencies disseminate respondent-level data with high utility and privacy protection …