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ABSI: An Adaptive Binary Splitting Algorithm for Malicious Meter Inspection in Smart Grid
Xia XF(夏小芳)1,2,3; Xiao Y(肖杨)3; Liang W(梁炜)1
Department工业控制网络与系统研究室
Source PublicationIEEE Transactions on Information Forensics and Security
ISSN1556-6013
2019
Volume14Issue:2Pages:445-458
Indexed BySCI ; EI
EI Accession number20182905554678
WOS IDWOS:000442348400001
Contribution Rank1
Funding OrganizationNational Key Research and Development Program of China ; U.S. National Science Foundation ; National Natural Science Foundation of China ; Smart Manufacturing Standardization Project of the Ministry of Industry and Information Technology of the People's Republic of China
KeywordElectricity Theft Smart Grid Security Group Testing
Abstract

Electricity theft is a widespread problem that causes tremendous economical losses for all utility companies around the globe. As many countries struggle to update their antique power systems to emerging smart grids, more and more smart meters are deployed throughout the world. Compared with analog meters which can be tampered with by only physical attacks, smart meters can be manipulated by malicious users with both physical and cyber attacks for the purpose of stealing electricity. Thus, electricity theft will become even more serious in a smart grid than in a traditional power system if utility companies do not implement efficient solutions. The goal of this paper is to identify all malicious users in a neighborhood area in a smart grid within the shortest detection time. We propose an Adaptive Binary Splitting Inspection (ABSI) algorithm which adopts a group testing method to locate the malicious users. There are two considered inspection strategies in this paper: a scanning method in which users will be inspected individually, and a binary search method by which a specific number of users will be examined as a whole. During the inspection process of our proposed scheme, the inspection strategy as well as the number of users in the groups to be inspected are adaptively adjusted. Simulation results show that the proposed ABSI algorithm outperforms existing methods.

Language英语
WOS SubjectComputer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS KeywordNontechnical Loss Fraud ; Neighborhood Area Networks ; Defective Members ; System ; Security ; Detector ; Scheme
WOS Research AreaComputer Science ; Engineering
Funding ProjectNational Key Research and Development Program of China[2017YFE0101300] ; U.S. National Science Foundation[CNS-1059265] ; National Natural Science Foundation of China[61374200] ; National Natural Science Foundation of China[71661147005] ; Smart Manufacturing Standardization Project of the Ministry of Industry and Information Technology of the People's Republic of China
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Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22150
Collection工业控制网络与系统研究室
Corresponding AuthorXiao Y(肖杨); Liang W(梁炜)
Affiliation1.Key Lab of Networked Control Systems and Shenyang Institute of Automation, Chinese Academy of Sciences, 110016 Shenyang, China
2.University of Chinese Academy of Sciences, 100039 Beijing, China
3.Department of Computer Science, The University of Alabama, Tuscaloosa, AL 35487-0290 USA
Recommended Citation
GB/T 7714
Xia XF,Xiao Y,Liang W. ABSI: An Adaptive Binary Splitting Algorithm for Malicious Meter Inspection in Smart Grid[J]. IEEE Transactions on Information Forensics and Security,2019,14(2):445-458.
APA Xia XF,Xiao Y,&Liang W.(2019).ABSI: An Adaptive Binary Splitting Algorithm for Malicious Meter Inspection in Smart Grid.IEEE Transactions on Information Forensics and Security,14(2),445-458.
MLA Xia XF,et al."ABSI: An Adaptive Binary Splitting Algorithm for Malicious Meter Inspection in Smart Grid".IEEE Transactions on Information Forensics and Security 14.2(2019):445-458.
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