Synthetic data generation with differential privacy via Bayesian networks

• المؤلفون الرئيسيون: Bao, Ergute, Xiao, Xiaokui, Zhao, Jun, Zhang, Dongping, Ding, Bolin
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Differential Privacy; Synthetic Data Generation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/164213

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.