{"title":"通过对电压/变压指令的文本分析检测智能逆变器网络攻击的大型语言模型","authors":"Alaa Selim;Junbo Zhao;Bo Yang","doi":"10.1109/TSG.2024.3453648","DOIUrl":null,"url":null,"abstract":"This letter demonstrates a proof-of-concept validation of the Large Language Model (LLM) for smart inverter cyberattack detection through textual control commands. The proposed method can detect the manipulation of Volt/VAR curves and the comparison results with state-of-the-art machine learning techniques highlight its efficacy in identifying cyber attacks. Test results obtained from a real distribution feeder in Colorado, USA, validate the high accuracy for attack classification as well as demonstrate the potential of LLMs in adding a robust security layer for cyber-attacks.","PeriodicalId":13331,"journal":{"name":"IEEE Transactions on Smart Grid","volume":"15 6","pages":"6179-6182"},"PeriodicalIF":8.6000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Large Language Model for Smart Inverter Cyber-Attack Detection via Textual Analysis of Volt/VAR Commands\",\"authors\":\"Alaa Selim;Junbo Zhao;Bo Yang\",\"doi\":\"10.1109/TSG.2024.3453648\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This letter demonstrates a proof-of-concept validation of the Large Language Model (LLM) for smart inverter cyberattack detection through textual control commands. The proposed method can detect the manipulation of Volt/VAR curves and the comparison results with state-of-the-art machine learning techniques highlight its efficacy in identifying cyber attacks. Test results obtained from a real distribution feeder in Colorado, USA, validate the high accuracy for attack classification as well as demonstrate the potential of LLMs in adding a robust security layer for cyber-attacks.\",\"PeriodicalId\":13331,\"journal\":{\"name\":\"IEEE Transactions on Smart Grid\",\"volume\":\"15 6\",\"pages\":\"6179-6182\"},\"PeriodicalIF\":8.6000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Smart Grid\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10663471/\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Smart Grid","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10663471/","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Large Language Model for Smart Inverter Cyber-Attack Detection via Textual Analysis of Volt/VAR Commands
This letter demonstrates a proof-of-concept validation of the Large Language Model (LLM) for smart inverter cyberattack detection through textual control commands. The proposed method can detect the manipulation of Volt/VAR curves and the comparison results with state-of-the-art machine learning techniques highlight its efficacy in identifying cyber attacks. Test results obtained from a real distribution feeder in Colorado, USA, validate the high accuracy for attack classification as well as demonstrate the potential of LLMs in adding a robust security layer for cyber-attacks.
期刊介绍:
The IEEE Transactions on Smart Grid is a multidisciplinary journal that focuses on research and development in the field of smart grid technology. It covers various aspects of the smart grid, including energy networks, prosumers (consumers who also produce energy), electric transportation, distributed energy resources, and communications. The journal also addresses the integration of microgrids and active distribution networks with transmission systems. It publishes original research on smart grid theories and principles, including technologies and systems for demand response, Advance Metering Infrastructure, cyber-physical systems, multi-energy systems, transactive energy, data analytics, and electric vehicle integration. Additionally, the journal considers surveys of existing work on the smart grid that propose new perspectives on the history and future of intelligent and active grids.