{"title":"基于硬件的智能电子设备识别","authors":"Girish Vaidya, T. Prabhakar","doi":"10.1109/iotdi54339.2022.00018","DOIUrl":null,"url":null,"abstract":"Modern power grid infrastructure utilises Intelligent Electronic Devices (IEDs) for sensing and control of the grid. IEDs continuously sense power related parameters through a multi-channel simultaneous sampling Analog to Digital Converter (ADC). The dependence on IEDs for the reliable operation of the grid mandates that these devices are irrefutably identified. In this work, we generate an IED identifier based on its innate properties. Our proposed approach is in-situ, non-invasive and does not require any special hardware. Through our evaluation over six weeks, we demonstrate the Repeatability, Uniqueness, Randomness and Real-time property of the identifier. Our evaluation results show that the repeatability of identifiers is 99.5% and together they could uniquely identify a few million devices. Furthermore, we also demonstrate a method to fingerprint Electro-magnetic relays (EMR), another essential component used inside IEDs. Defective EMRs, along with replacement from a different family can be identified.","PeriodicalId":314074,"journal":{"name":"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Hardware based identification for Intelligent Electronic Devices\",\"authors\":\"Girish Vaidya, T. Prabhakar\",\"doi\":\"10.1109/iotdi54339.2022.00018\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern power grid infrastructure utilises Intelligent Electronic Devices (IEDs) for sensing and control of the grid. IEDs continuously sense power related parameters through a multi-channel simultaneous sampling Analog to Digital Converter (ADC). The dependence on IEDs for the reliable operation of the grid mandates that these devices are irrefutably identified. In this work, we generate an IED identifier based on its innate properties. Our proposed approach is in-situ, non-invasive and does not require any special hardware. Through our evaluation over six weeks, we demonstrate the Repeatability, Uniqueness, Randomness and Real-time property of the identifier. Our evaluation results show that the repeatability of identifiers is 99.5% and together they could uniquely identify a few million devices. Furthermore, we also demonstrate a method to fingerprint Electro-magnetic relays (EMR), another essential component used inside IEDs. Defective EMRs, along with replacement from a different family can be identified.\",\"PeriodicalId\":314074,\"journal\":{\"name\":\"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iotdi54339.2022.00018\",\"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/ACM Seventh International Conference on Internet-of-Things Design and Implementation (IoTDI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iotdi54339.2022.00018","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Hardware based identification for Intelligent Electronic Devices
Modern power grid infrastructure utilises Intelligent Electronic Devices (IEDs) for sensing and control of the grid. IEDs continuously sense power related parameters through a multi-channel simultaneous sampling Analog to Digital Converter (ADC). The dependence on IEDs for the reliable operation of the grid mandates that these devices are irrefutably identified. In this work, we generate an IED identifier based on its innate properties. Our proposed approach is in-situ, non-invasive and does not require any special hardware. Through our evaluation over six weeks, we demonstrate the Repeatability, Uniqueness, Randomness and Real-time property of the identifier. Our evaluation results show that the repeatability of identifiers is 99.5% and together they could uniquely identify a few million devices. Furthermore, we also demonstrate a method to fingerprint Electro-magnetic relays (EMR), another essential component used inside IEDs. Defective EMRs, along with replacement from a different family can be identified.