Differentially Private Release of Datasets using Gaussian Copula
We propose a generic mechanism to efficiently release differentially private synthetic versions of high-dimensional datasets with high utility. The core technique in our mechanism is the use of copulas, which are functions representing dependencies among random variables with a multivariate distribu...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Labor Dynamics Institute
2020-06-01
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| Series: | The Journal of Privacy and Confidentiality |
| Subjects: | |
| Online Access: | https://journalprivacyconfidentiality.org/index.php/jpc/article/view/686 |