PrivEval: a tool for interactive evaluation of privacy metrics in synthetic data generation
Summary: PrivEval is an interactive tool for evaluating privacy properties of synthetic datasets that implements and validates multiple privacy metrics (per-user and dataset-level) to characterize how DP noise affects the privacy–utility tradeoff. It also checks each metric’s assumptions to surface limitations and improve transparency and usability for practitioners. (summarized by gpt-5-mini on Feb 09 2026)
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 2,421 | Data Synthesis based on Generative Adversarial Networks | 2018 | VLDB | 8.8514021e-05 |
| 4,252 | DPSynthesizer: Differentially Private Data Synthesizer for Privacy Preserving Data Sharing | 2014 | VLDB | 6.3233894e-05 |
| 5,080 | Exploring Privacy-Accuracy Tradeoffs using DPComp | 2016 | SIGMOD | 5.7137145e-05 |
| 7,502 | PSynDB: Accurate and Accessible Private Data Generation | 2019 | VLDB | 4.7180617e-05 |
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