{"title":"高级计量基础设施的轻量级安全性","authors":"Mohsin Kamal, M. Tariq","doi":"10.1109/VTCSpring.2019.8746620","DOIUrl":null,"url":null,"abstract":"Smart meters (SMs) in Advanced Metering Infrastructure (AMI) are physically accessible due to which the protection against eavesdropping of AMI and energy theft control have gained utmost importance. A light-weight security solution is the requirement for AMI networks because of the small size and less computational capabilities of SMs. To address this problem, a light-weight security solution is proposed in this paper to detect any adversarial node in between two SMs. Through the proposed algorithms, adversarial node can be detected in AMI. Received Signal Strength Indicator (RSSI) is used to generate link fingerprints after every 60 seconds, which are sent to the Data Concentrator Unit (DCU). The DCU applies these algorithms on the received link fingerprints in order to detect any unwanted activity. MICAz motes are used as communication module of SM and adversary to generate RSSI values. These RSSI values are simulated in MATLAB in which it detects adversarial node or meter tempering with 100% accuracy by getting values other than 0 and 1 as the average of consecutive RSSI and distance between the RSSI of connected SMs.","PeriodicalId":134773,"journal":{"name":"2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Light-Weight Security for Advanced Metering Infrastructure\",\"authors\":\"Mohsin Kamal, M. Tariq\",\"doi\":\"10.1109/VTCSpring.2019.8746620\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Smart meters (SMs) in Advanced Metering Infrastructure (AMI) are physically accessible due to which the protection against eavesdropping of AMI and energy theft control have gained utmost importance. A light-weight security solution is the requirement for AMI networks because of the small size and less computational capabilities of SMs. To address this problem, a light-weight security solution is proposed in this paper to detect any adversarial node in between two SMs. Through the proposed algorithms, adversarial node can be detected in AMI. Received Signal Strength Indicator (RSSI) is used to generate link fingerprints after every 60 seconds, which are sent to the Data Concentrator Unit (DCU). The DCU applies these algorithms on the received link fingerprints in order to detect any unwanted activity. MICAz motes are used as communication module of SM and adversary to generate RSSI values. These RSSI values are simulated in MATLAB in which it detects adversarial node or meter tempering with 100% accuracy by getting values other than 0 and 1 as the average of consecutive RSSI and distance between the RSSI of connected SMs.\",\"PeriodicalId\":134773,\"journal\":{\"name\":\"2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/VTCSpring.2019.8746620\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 89th Vehicular Technology Conference (VTC2019-Spring)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/VTCSpring.2019.8746620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
高级计量基础设施(AMI)中的智能电表(SMs)具有物理可访问性,因此防止AMI窃听和能源盗窃控制变得至关重要。轻量级的安全解决方案是AMI网络的需求,因为SMs的尺寸小,计算能力低。为了解决这个问题,本文提出了一个轻量级的安全解决方案来检测两个SMs之间的任何对抗节点。通过本文提出的算法,可以检测到AMI中的对抗节点。RSSI (Received Signal Strength Indicator)是指每隔60秒生成一次链路指纹,发送给DCU (Data Concentrator Unit)。DCU在接收到的链路指纹上应用这些算法,以便检测任何不需要的活动。利用MICAz粒子作为SM和对手的通信模块,生成RSSI值。这些RSSI值在MATLAB中进行仿真,通过获取除0和1以外的值作为连续RSSI的平均值和连接SMs的RSSI之间的距离,以100%的准确率检测对抗性节点或仪表回弹。
Light-Weight Security for Advanced Metering Infrastructure
Smart meters (SMs) in Advanced Metering Infrastructure (AMI) are physically accessible due to which the protection against eavesdropping of AMI and energy theft control have gained utmost importance. A light-weight security solution is the requirement for AMI networks because of the small size and less computational capabilities of SMs. To address this problem, a light-weight security solution is proposed in this paper to detect any adversarial node in between two SMs. Through the proposed algorithms, adversarial node can be detected in AMI. Received Signal Strength Indicator (RSSI) is used to generate link fingerprints after every 60 seconds, which are sent to the Data Concentrator Unit (DCU). The DCU applies these algorithms on the received link fingerprints in order to detect any unwanted activity. MICAz motes are used as communication module of SM and adversary to generate RSSI values. These RSSI values are simulated in MATLAB in which it detects adversarial node or meter tempering with 100% accuracy by getting values other than 0 and 1 as the average of consecutive RSSI and distance between the RSSI of connected SMs.