The Risk-Utility Tradeoff for Data Privacy Models
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Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/7791100/7792416/07792481.pdf?arnumber=7792481
Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. On the Complexity of Optimal k-Anonymity: A New Proof Based on Graph Coloring;IEEE Access;2024
2. Assessing the Potentials of LLMs and GANs as State-of-the-Art Tabular Synthetic Data Generation Methods;Lecture Notes in Computer Science;2024
3. A hybrid anonymization pipeline to improve the privacy-utility balance in sensitive datasets for ML purposes;Proceedings of the 18th International Conference on Availability, Reliability and Security;2023-08-29
4. A Computational Framework for Preserving Privacy and Maintaining Utility of Geographically Aggregated Data: A Stochastic Spatial Optimization Approach;Annals of the American Association of Geographers;2023-03-20
5. A New Anonymization Model for Privacy Preserving Data Publishing: CANON;Balkan Journal of Electrical and Computer Engineering;2022-07-17
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