{"title":"基于网络安全视角的智能电网异常检测研究*","authors":"Ahmad N. Alkuwari, S. Al-Kuwari, M. Qaraqe","doi":"10.1109/SGRE53517.2022.9774221","DOIUrl":null,"url":null,"abstract":"Smart grid is the next generation for power generation, consumption and distribution. However, with the introduction of smart communication in such sensitive components, major risks from cybersecurity perspective quickly emerged. This survey reviews and reports on the state-of-the-art techniques for detecting cyber attacks in smart grids, mainly through machine learning techniques.","PeriodicalId":64562,"journal":{"name":"智能电网与可再生能源(英文)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Anomaly Detection in Smart Grids: A Survey From Cybersecurity Perspective*\",\"authors\":\"Ahmad N. Alkuwari, S. Al-Kuwari, M. Qaraqe\",\"doi\":\"10.1109/SGRE53517.2022.9774221\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart grid is the next generation for power generation, consumption and distribution. However, with the introduction of smart communication in such sensitive components, major risks from cybersecurity perspective quickly emerged. This survey reviews and reports on the state-of-the-art techniques for detecting cyber attacks in smart grids, mainly through machine learning techniques.\",\"PeriodicalId\":64562,\"journal\":{\"name\":\"智能电网与可再生能源(英文)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"智能电网与可再生能源(英文)\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://doi.org/10.1109/SGRE53517.2022.9774221\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"智能电网与可再生能源(英文)","FirstCategoryId":"1087","ListUrlMain":"https://doi.org/10.1109/SGRE53517.2022.9774221","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Anomaly Detection in Smart Grids: A Survey From Cybersecurity Perspective*
Smart grid is the next generation for power generation, consumption and distribution. However, with the introduction of smart communication in such sensitive components, major risks from cybersecurity perspective quickly emerged. This survey reviews and reports on the state-of-the-art techniques for detecting cyber attacks in smart grids, mainly through machine learning techniques.
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