{"title":"基于群体智能的智能电表异常检测算法","authors":"Pradeep Subhash Paikrao, R. Bose","doi":"10.1145/3243318.3243319","DOIUrl":null,"url":null,"abstract":"Advancement in the information and communication technology has introduced Advanced Metering Infrastructure (AMI) in the electricity metering system, which has replaced old mechanical meters with smart electric meters. This modernization also introduced a lot of scope for the different anomalies and attacks on smart meters. Hence to tackle these challenges, we have proposed three anomaly detection algorithms (VBA, HBA, KBA) which are truly based on the principles of Swarm Intelligence (SI). The swarm intelligence is the emerging subbranch of artificial intelligence which studies the collective intelligence of groups of simple agents. The theory is corroborated by its performance in terms of probability of detection and probability of false alarm. The proposed algorithms entrust the probability of detection and probability of false alarm close to 1.00 and 0.17 respectively.","PeriodicalId":313677,"journal":{"name":"Proceedings of the 1st International Workshop on Future Industrial Communication Networks","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Anomaly Detection Algorithms for Smart Metering using Swarm Intelligence\",\"authors\":\"Pradeep Subhash Paikrao, R. Bose\",\"doi\":\"10.1145/3243318.3243319\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Advancement in the information and communication technology has introduced Advanced Metering Infrastructure (AMI) in the electricity metering system, which has replaced old mechanical meters with smart electric meters. This modernization also introduced a lot of scope for the different anomalies and attacks on smart meters. Hence to tackle these challenges, we have proposed three anomaly detection algorithms (VBA, HBA, KBA) which are truly based on the principles of Swarm Intelligence (SI). The swarm intelligence is the emerging subbranch of artificial intelligence which studies the collective intelligence of groups of simple agents. The theory is corroborated by its performance in terms of probability of detection and probability of false alarm. The proposed algorithms entrust the probability of detection and probability of false alarm close to 1.00 and 0.17 respectively.\",\"PeriodicalId\":313677,\"journal\":{\"name\":\"Proceedings of the 1st International Workshop on Future Industrial Communication Networks\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 1st International Workshop on Future Industrial Communication Networks\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3243318.3243319\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 1st International Workshop on Future Industrial Communication Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3243318.3243319","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Anomaly Detection Algorithms for Smart Metering using Swarm Intelligence
Advancement in the information and communication technology has introduced Advanced Metering Infrastructure (AMI) in the electricity metering system, which has replaced old mechanical meters with smart electric meters. This modernization also introduced a lot of scope for the different anomalies and attacks on smart meters. Hence to tackle these challenges, we have proposed three anomaly detection algorithms (VBA, HBA, KBA) which are truly based on the principles of Swarm Intelligence (SI). The swarm intelligence is the emerging subbranch of artificial intelligence which studies the collective intelligence of groups of simple agents. The theory is corroborated by its performance in terms of probability of detection and probability of false alarm. The proposed algorithms entrust the probability of detection and probability of false alarm close to 1.00 and 0.17 respectively.