南京理工大学学报（自然科学版）2019，Vol.43Issue(5)：571-577,7.DOI:10.14177/j.cnki.32-1397n.2019.43.05.005
面向电力工控网络大数据的微聚集差分隐私保护方法
Micro-aggregation for differential privacy protection method based on big data of power control network
程伟华 1谭晶 1徐明生 1倪震2
作者信息
- 1. 江苏电力信息技术有限公司,江苏 南京210024
- 2. 南京晓庄学院 信息工程学院,江苏 南京211171
- 折叠
摘要
Abstract
In order to solve the problem of privacy disclosure of network, the differential privacy protection in frequent pattern mining is implemented based on the micro-aggregation algorithm for the power industrial control network to ensure the balance among information release, data analysis requirements and privacy protection demands by weighting the exponential mechanism and the micro-aggregation weight of each mode. By adding the Laplace noise disturbance, the Top-k frequent pattern method is selected and the original support each of the selected mode achieves a balance between privacy and utility. The method in this paper can guarantee the trust of all parties in the power industrial control system and the healthy growth of power industrial control system. The experimental results on the dataset verify the effectiveness of the method.关键词
微聚集/匿名化/频繁模式挖掘/差分隐私保护Key words
micro-aggregation/anonymization/frequent pattern mining/differential privacy protection分类
信息技术与安全科学引用本文复制引用
程伟华,谭晶,徐明生,倪震..面向电力工控网络大数据的微聚集差分隐私保护方法[J].南京理工大学学报（自然科学版）,2019,43(5):571-577,7.
