文献类型：期刊文献

英文题名：False-Data-Injection-Enabled Network Parameter Modifications in Power Systems: Attack and Detection

作者：Liu, Chensheng[1];He, Wangli[1];Deng, Ruilong[2,3];Tian, Yu-Chu[4];Du, Wenli[1]

机构：[1]East China Univ Sci & Technol, Key Lab Smart Mfg Energy Chem Proc, Minist Educ, Shanghai 200237, Peoples R China;[2]Zhejiang Univ, State Key Lab Ind Control Technol, Hangzhou 310027, Peoples R China;[3]Zhejiang Univ, Coll Control Sci & Engn, Hangzhou 310027, Peoples R China;[4]Queensland Univ Technol, Sch Comp Sci, Brisbane, Qld 4001, Australia

年份：2023

卷号：19

期号：1

起止页码：177

外文期刊名：IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS

收录：;EI(收录号：20222012126844);WOS:【SCI-EXPANDED(收录号:WOS:000880654600020)】；

基金：This work was supported in part by the National Natural Science Foundation of China (Basic Science Center Program) under Grant 61988101, in part by the National Natural Science Foundation of China under Grant 62073138, in part by the National Science Foundation for Excellent Young Scholars under Grant 61922030, in part by the National Natural Science Foundation of China under Grant 62073285, and in part by Shanghai AI Lab. Paper no. TII-21-3980.

语种：英文

外文关键词：State estimation; Power systems; Power measurement; Biological system modeling; Measurement uncertainty; Databases; Data models; False data injection (FDI) attack; indirect modifications of network parameters; optimal detection strategy; security of cyber-physical systems

摘要：Due to the close relevance to the reliability and efficiency of power systems, network parameters such as branch admittance have been the target of various cyberattacks. However, existing attack models are generally based on the impractical assumption that attackers can directly modify the data of network parameter stored in well-secured control centers. This article proposes a practical attack model and designs an optimal strategy to detect malicious modification of critical network parameters. Specifically, the vulnerability of network parameter error processing is discovered and exploited to indirectly modify the data of network parameter without accessing to the well-secured control center. A model of false-data-injection-enabled network parameter modification is proposed, which significantly reduces the requirements on attackers' capability and system information. An optimal detection strategy is designed based on the analysis of the minimal protection set at a single branch, which can significantly reduce the number of protected measurements in detecting malicious modification of critical network parameters. Finally, numerical simulations are carried out on the PJM 5-bus and the IEEE 118-bus test systems to validate the theoretical results.