Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata-Reference-Cited by-同舟云学术

Comparing the Utility and Disclosure Risk of Synthetic Data with Samples of Microdata

Published:2022 Issue: Volume: Page:234-249
ISSN:0302-9743
Container-title:Privacy in Statistical Databases
language:
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Author:

Little Claire^ORCID,Elliot Mark^ORCID,Allmendinger Richard^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-13945-1_17

Reference47 articles.

1. Benedetto, G., Stinson, M.H., Abowd, J.M.: The creation and use of the SIPP synthetic beta. Technical report, November, U.S. Census Bureau (2018)

2. Breiman, L., Friedman, J., Stone, C.J., Olshen, R.A.: Classification and regression trees. Wadsworth International Group, Belmont, California (1984). https://doi.org/10.1201/9781315139470

3. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001). https://doi.org/10.1023/A:1010933404324

4. Caiola, G., Reiter, J.P.: Random forests for generating partially synthetic, categorical data. Trans. Data Privacy 3(1), 27–42 (2010)

5. Camino, R., Hammerschmidt, C., State, R.: Generating multi-categorical samples with generative adversarial networks. arXiv preprint arXiv:1807.01202 (2018)

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