Thusitha Dayaratne, C. Rudolph, A. Liebman, Mahsa Salehi
{"title":"我们可以付出更少:针对智能电网居民需求响应的协同假数据注入攻击","authors":"Thusitha Dayaratne, C. Rudolph, A. Liebman, Mahsa Salehi","doi":"10.1145/3422337.3447826","DOIUrl":null,"url":null,"abstract":"Advanced metering infrastructure, along with home automation processes, is enabling more efficient and effective demand-side management opportunities for both consumers and utility companies. However, tight cyber-physical integration also enables novel attack vectors for false data injection attacks (FDIA) as home automation/ home energy management systems reside outside the utilities' control perimeter. Authentic users themselves can manipulate these systems without causing significant security breaches compared to traditional FDIAs. This work depicts a novel FDIA that exploits one of the commonly utilised distributed device scheduling architectures. We evaluate the attack impact using a realistic dataset to demonstrate that adversaries gain significant benefits, independently from the actual algorithm used for optimisation, as long as they have control over a sufficient amount of demand. Compared to traditional FDIAs, reliable security mechanisms such as proper authentication, security protocols, security controls or, sealed/controlled devices cannot prevent this new type of FDIA. Thus, we propose a set of possible impact alleviation solutions to thwart this type of attack.","PeriodicalId":187272,"journal":{"name":"Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy","volume":"463 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"We Can Pay Less: Coordinated False Data Injection Attack Against Residential Demand Response in Smart Grids\",\"authors\":\"Thusitha Dayaratne, C. Rudolph, A. Liebman, Mahsa Salehi\",\"doi\":\"10.1145/3422337.3447826\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Advanced metering infrastructure, along with home automation processes, is enabling more efficient and effective demand-side management opportunities for both consumers and utility companies. However, tight cyber-physical integration also enables novel attack vectors for false data injection attacks (FDIA) as home automation/ home energy management systems reside outside the utilities' control perimeter. Authentic users themselves can manipulate these systems without causing significant security breaches compared to traditional FDIAs. This work depicts a novel FDIA that exploits one of the commonly utilised distributed device scheduling architectures. We evaluate the attack impact using a realistic dataset to demonstrate that adversaries gain significant benefits, independently from the actual algorithm used for optimisation, as long as they have control over a sufficient amount of demand. Compared to traditional FDIAs, reliable security mechanisms such as proper authentication, security protocols, security controls or, sealed/controlled devices cannot prevent this new type of FDIA. Thus, we propose a set of possible impact alleviation solutions to thwart this type of attack.\",\"PeriodicalId\":187272,\"journal\":{\"name\":\"Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy\",\"volume\":\"463 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-04-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3422337.3447826\",\"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 Eleventh ACM Conference on Data and Application Security and Privacy","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3422337.3447826","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We Can Pay Less: Coordinated False Data Injection Attack Against Residential Demand Response in Smart Grids
Advanced metering infrastructure, along with home automation processes, is enabling more efficient and effective demand-side management opportunities for both consumers and utility companies. However, tight cyber-physical integration also enables novel attack vectors for false data injection attacks (FDIA) as home automation/ home energy management systems reside outside the utilities' control perimeter. Authentic users themselves can manipulate these systems without causing significant security breaches compared to traditional FDIAs. This work depicts a novel FDIA that exploits one of the commonly utilised distributed device scheduling architectures. We evaluate the attack impact using a realistic dataset to demonstrate that adversaries gain significant benefits, independently from the actual algorithm used for optimisation, as long as they have control over a sufficient amount of demand. Compared to traditional FDIAs, reliable security mechanisms such as proper authentication, security protocols, security controls or, sealed/controlled devices cannot prevent this new type of FDIA. Thus, we propose a set of possible impact alleviation solutions to thwart this type of attack.