电力系统自动化2018，Vol.42Issue(2)：121-127,7.DOI:10.7500/AEPS20170611006
差分隐私保护下面向海量用户的用电数据聚类分析
Differential Privacy Protection Based Clustering Analysis of Electricity Consumption Data for Massive Consumers
摘要
Abstract
Smart meter achieves real-time and comprehensive collection of user"s electricity consumption information.It is possible to accurately do clustering analysis of the user"s electrical behavior by using such data.However,in the process,the user"s information can be leaked easily.So a method of differential privacy clustering analysis for electricity information is proposed.It utilizes two phase privacy protection clustering to solve the contradiction that privacy protection and accurate analysis cannot coexist.Two phase clustering adopting the distributed computation idea consists of local clustering and global clustering.The former uses differential privacy adaptive K-means algorithm to complete first cluster electricity consumption data collected by smart meter.In global clustering,a new clustering algorithm based on density and hierarchy is designed to optimize the results from local clustering.Relevant experiments show that this method is effective.关键词
隐私保护/聚类分析/用电数据/分布式计算Key words
privacy protection/clustering analysis/electricity consumption data/distributed computation引用本文复制引用
王保义,胡恒,张少敏..差分隐私保护下面向海量用户的用电数据聚类分析[J].电力系统自动化,2018,42(2):121-127,7.基金项目
国家自然科学基金资助项目(61502168) （61502168）
河北省自然科学基金资助项目(F2016502069). This work is supported by National Natural Science Foundation of China (No.61502168) and Hebei Provincial Natural Science Foundation of China(No.F2016502069). （F2016502069）
