A novel detector to detect colluded non-technical loss frauds in smart grid

被引:27
作者
Han, Wenlin [2 ]
Xiao, Yang [1 ,2 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Peoples R China
[2] Univ Alabama, Dept Comp Sci, Tuscaloosa, AL 35487 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
Smart grid security; Smart meter; Non-technical loss; Colluded fraud; Malicious meter; V2G NETWORKS; ALGORITHM; SECURITY; ISSUES;
D O I
10.1016/j.comnet.2016.10.011
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
A Non-Technical Loss (NTL) fraud occurs when a fraudster tampers with a smart meter so that the meter registers less electricity consumption than the actual consumed amount, and therefore the utility becomes the victim who suffers the corresponding economic loss. In the literature, many detection schemes have been proposed to detect NTL frauds. However, some NTL frauds are far more complicated than what the existing schemes expect. We recently discovered a new potential type of frauds, a variant of NTL frauds, called Colluded Non-Technical Loss (CNTL) frauds in the Smart Grid. In a CNTL fraud, multiple fraudsters can co-exist or collaborate to commit the fraud. Existing detection schemes cannot detect CNTL frauds since these methods do not consider the co-existing or collaborating fraudsters, and therefore cannot distinguish one from many fraudsters. In this paper, we propose a CNTL fraud detector to detect CNTL frauds. The proposed method can quickly detect a tampered meter based on recursive least squares. After identifying the tampered meter, the proposed scheme can detect different fraudsters using mathematical models. Our experiments show that our method is effective in detecting CNTL frauds. (C) 2016 Elsevier B.V. All rights reserved.
引用
收藏
页码:19 / 31
页数:13
相关论文
共 47 条
[11]   SCADA communication and security issues [J].
Gao, Jingcheng ;
Liu, Jing ;
Rajan, Bharat ;
Nori, Rahul ;
Fu, Bo ;
Xiao, Yang ;
Liang, Wei ;
Chen, C. L. Philip .
SECURITY AND COMMUNICATION NETWORKS, 2014, 7 (01) :175-194
[12]   A survey of communication/networking in Smart Grids [J].
Gao, Jingcheng ;
Xiao, Yang ;
Liu, Jing ;
Liang, Wei ;
Chen, C. L. Philip .
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2012, 28 (02) :391-404
[13]   SUPERVISORY CONTROL AND DATA ACQUISITION [J].
GAUSHELL, DJ ;
DARLINGTON, HT .
PROCEEDINGS OF THE IEEE, 1987, 75 (12) :1645-1658
[14]   Structural Minimax Probability Machine [J].
Gu, Bin ;
Sun, Xingming ;
Sheng, Victor S. .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (07) :1646-1656
[15]   Incremental Support Vector Learning for Ordinal Regression [J].
Gu, Bin ;
Sheng, Victor S. ;
Tay, Keng Yeow ;
Romano, Walter ;
Li, Shuo .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2015, 26 (07) :1403-1416
[16]  
Habrail Georges., 2012, Individual household electric power consumption data set
[17]  
Han W., 2016, P INT WORKSH TRAFF M
[18]   Design a fast Non-Technical Loss fraud detector for smart grid [J].
Han, Wenlin ;
Xiao, Yang .
SECURITY AND COMMUNICATION NETWORKS, 2016, 9 (18) :5116-5132
[19]   CNFD: A Novel Scheme to Detect Colluded Non-technical Loss Fraud in Smart Grid [J].
Han, Wenlin ;
Xiao, Yang .
WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS, WASA 2016, 2016, 9798 :47-55
[20]   Privacy preservation for V2G networks in smart grid: A survey [J].
Han, Wenlin ;
Xiao, Yang .
COMPUTER COMMUNICATIONS, 2016, 91-92 :17-28