Synthetic data generation with differential privacy via Bayesian networks
This paper describes PrivBayes, a differentially private method for generating synthetic datasets that was used in the 2018 Differential Privacy Synthetic Data Challenge organized by NIST.
Main Authors: | Bao, Ergute, Xiao, Xiaokui, Zhao, Jun, Zhang, Dongping, Ding, Bolin |
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Other Authors: | School of Computer Science and Engineering |
Format: | Journal Article |
Language: | English |
Published: |
2023
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Subjects: | |
Online Access: | https://hdl.handle.net/10356/164213 |
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