Achieving privacy-preserving big data aggregation with fault tolerance in smart grid

作     者：Zhitao Guan Guanlin Si 

作者机构：School of Control and Computer Engineerir~ North China Electric Power University Belting 102206 China 

出 版 物：《Digital Communications and Networks》 (数字通信与网络（英文版）)

年 卷 期：2017年第3卷第4期

页      面：242-249页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 

基　　金：National Natural Science Foundation of China, NSFC, (61402171) Fundamental Research Funds for the Central Universities, (2016MS29) 

主　　题：Big data Smart grid Privacy-preserving Fault tolerance 

摘      要：In a smart grid, a huge amount of data is collected for various applications, such as load monitoring and demand response. These data are used for analyzing the power state and formulating the optimal dispatching strategy. However, these big energy data in terms of volume, velocity and variety raise concern over consumers＇ privacy. For instance, in order to optimize energy utilization and support demand response, numerous smart meters are installed at a consumer＇s home to collect energy consumption data at a fine granularity, but these fine-grained data may contain information on the appliances and thus the consumer＇s behaviors at home. In this paper, we propose a privacy-preserving data aggregation scheme based on secret sharing with fault tolerance in a smart grid, which ensures that the control center obtains the integrated data without compromising privacy. Meanwhile, we also consider fault tolerance and resistance to differential attack during the data aggregation. Finally, we perform a security analysis and performance evaluation of our scheme in comparison with the other similar schemes. The analysis shows that our scheme can meet the security requirement, and it also shows better performance than other popular methods.