DP-Select: Improving Utility and Privacy in Tabular Data Synthesis with Differentially Private Generative Adversarial Networks and Differentially Private Selection
| dc.contributor.author | Ebrahimianghazani, Faezeh | |
| dc.date.accessioned | 2023-05-29T18:27:32Z | |
| dc.date.available | 2023-05-29T18:27:32Z | |
| dc.date.issued | 2023-05-29 | |
| dc.date.submitted | 2023-05-19 | |
| dc.description.abstract | This thesis proposes DP-Select, a novel approach to tabular data synthesis that combines DP-GAN and differentially private selection. We develop a mutual information-based selection method that is flexible and scalable for high-dimensional data and large numbers of marginals while being differentially private. We evaluate DP-Select on various datasets and demonstrate its effectiveness and utility compared to existing DP-GAN methods. Our results indicate that DP-Select significantly enhances the utility of synthesized data while maintaining strong privacy guarantees, making it a promising extension of DP-GANs for privacy-preserving data synthesis in terms of differential privacy. We also show that DP-Select performs better for smaller privacy budgets, making it an attractive option for scenarios with limited privacy budgets. | en |
| dc.identifier.uri | http://hdl.handle.net/10012/19503 | |
| dc.language.iso | en | en |
| dc.pending | false | |
| dc.publisher | University of Waterloo | en |
| dc.subject | data synthesis | en |
| dc.subject | differential privacy | en |
| dc.subject | generative adversarial network | en |
| dc.subject | differentially private selection | en |
| dc.subject | exponential mechanism | en |
| dc.subject | data privacy | en |
| dc.subject | tabular data | en |
| dc.title | DP-Select: Improving Utility and Privacy in Tabular Data Synthesis with Differentially Private Generative Adversarial Networks and Differentially Private Selection | en |
| dc.type | Master Thesis | en |
| uws-etd.degree | Master of Mathematics | en |
| uws-etd.degree.department | David R. Cheriton School of Computer Science | en |
| uws-etd.degree.discipline | Computer Science | en |
| uws-etd.degree.grantor | University of Waterloo | en |
| uws-etd.embargo.terms | 0 | en |
| uws.contributor.advisor | Kerschbaum, Florian | |
| uws.contributor.affiliation1 | Faculty of Mathematics | en |
| uws.peerReviewStatus | Unreviewed | en |
| uws.published.city | Waterloo | en |
| uws.published.country | Canada | en |
| uws.published.province | Ontario | en |
| uws.scholarLevel | Graduate | en |
| uws.typeOfResource | Text | en |