{"title":"AMI中基于统计距离的盗窃检测器最小化能源盗窃","authors":"S. Singh, R. Bose, A. Joshi","doi":"10.1109/NCC.2018.8600016","DOIUrl":null,"url":null,"abstract":"To minimize energy theft attacks in Advanced Metering Infrastructure (AMI), we propose statistical distance based theft detection method. In the proposed method, different statistical distance indices (Jensen-Shannon distance, Hellinger distance, and Cumulative Distribution Function based distance) are computed using historical measurement variations between adjacent time steps. When adversary launches energy theft attacks in AMI, distance indices increases. A threshold is set to detect malicious measurement samples. We tested the performance of the proposed method under different attack scenario using real smart meter data. Test results show that the proposed method minimizes energy theft attacks efficiently.","PeriodicalId":121544,"journal":{"name":"2018 Twenty Fourth National Conference on Communications (NCC)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Minimizing Energy Theft by Statistical Distance based Theft Detector in AMI\",\"authors\":\"S. Singh, R. Bose, A. Joshi\",\"doi\":\"10.1109/NCC.2018.8600016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To minimize energy theft attacks in Advanced Metering Infrastructure (AMI), we propose statistical distance based theft detection method. In the proposed method, different statistical distance indices (Jensen-Shannon distance, Hellinger distance, and Cumulative Distribution Function based distance) are computed using historical measurement variations between adjacent time steps. When adversary launches energy theft attacks in AMI, distance indices increases. A threshold is set to detect malicious measurement samples. We tested the performance of the proposed method under different attack scenario using real smart meter data. Test results show that the proposed method minimizes energy theft attacks efficiently.\",\"PeriodicalId\":121544,\"journal\":{\"name\":\"2018 Twenty Fourth National Conference on Communications (NCC)\",\"volume\":\"61 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 Twenty Fourth National Conference on Communications (NCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NCC.2018.8600016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Twenty Fourth National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2018.8600016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Minimizing Energy Theft by Statistical Distance based Theft Detector in AMI
To minimize energy theft attacks in Advanced Metering Infrastructure (AMI), we propose statistical distance based theft detection method. In the proposed method, different statistical distance indices (Jensen-Shannon distance, Hellinger distance, and Cumulative Distribution Function based distance) are computed using historical measurement variations between adjacent time steps. When adversary launches energy theft attacks in AMI, distance indices increases. A threshold is set to detect malicious measurement samples. We tested the performance of the proposed method under different attack scenario using real smart meter data. Test results show that the proposed method minimizes energy theft attacks efficiently.