{"title":"针对直流微电网虚假数据注入攻击的分布式数据恢复","authors":"Zexuan Jin, Mengxiang Liu, Ruilong Deng, Peng Cheng","doi":"10.1109/SmartGridComm52983.2022.9960968","DOIUrl":null,"url":null,"abstract":"With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments.","PeriodicalId":252202,"journal":{"name":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Distributed Data Recovery Against False Data Injection Attacks in DC Microgrids\",\"authors\":\"Zexuan Jin, Mengxiang Liu, Ruilong Deng, Peng Cheng\",\"doi\":\"10.1109/SmartGridComm52983.2022.9960968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments.\",\"PeriodicalId\":252202,\"journal\":{\"name\":\"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)\",\"volume\":\"101 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SmartGridComm52983.2022.9960968\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SmartGridComm52983.2022.9960968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed Data Recovery Against False Data Injection Attacks in DC Microgrids
With the development of information and communications technology (ICT) in DC microgrids (DCmGs), the threat of false data injection attacks (FDIAs) is becoming more and more serious. However, the existing literature mainly focuses on the detection and identification of FDIAs in DCmGs, while the data recovery after the perception of FDIAs has never been thor-oughly investigated yet. In this paper, we propose a distributed data recovery scheme to eliminate the adverse impact caused by FDIAs in DCmGs. Firstly, by observing the point of common coupling (PCC) voltage under FDIAs, the injected constant bias can be roughly estimated. In order to obtain the precise constant bias, the mean filter (MF) is adopted to handle the measurement noises and small oscillations. Then, the estimated precise constant bias is compensated for the communicated signal to eliminate the attack impact. Furthermore, our proposed data recovery scheme, which only needs local information, is fully distributed. Finally, the accuracy and effectiveness of the distributed data recovery scheme are evaluated through systematical hardware-in-the-loop (HIL) experiments.