自动发电控制系统入侵检测和缓解框架

Fazel Mohammadi;Mehrdad Saif
{"title":"自动发电控制系统入侵检测和缓解框架","authors":"Fazel Mohammadi;Mehrdad Saif","doi":"10.1109/TICPS.2024.3452681","DOIUrl":null,"url":null,"abstract":"The main role of Automatic Generation Control (AGC) is to maintain power grids frequency within specified operating limits. Due to the fact that AGC is the sole automatic feedback control loop between physical and cyber infrastructure in modern power systems and the data required by the AGC system is transferred to a control center through communication links, it can be highly vulnerable to malicious attacks. Therefore, AGC systems should be well-protected against cyberattacks, e.g., False Data Injection (FDI) attacks. In this paper, an intrusion detection and mitigation framework for AGC systems based on a modified Goertzel algorithm is proposed. Compared with the existing intrusion detection and mitigation strategies, the major superiorities of the proposed framework are less computational burden, high accuracy, and rapid detection and mitigation of FDI attacks, which are considered unknown inputs. The proposed framework is validated on a two-area interconnected power systems model and the IEEE 39-bus test system. The dynamic simulation results under different testing conditions verify the applicability and effectiveness of the proposed framework.","PeriodicalId":100640,"journal":{"name":"IEEE Transactions on Industrial Cyber-Physical Systems","volume":"2 ","pages":"412-421"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Intrusion Detection and Mitigation Framework for Automatic Generation Control Systems\",\"authors\":\"Fazel Mohammadi;Mehrdad Saif\",\"doi\":\"10.1109/TICPS.2024.3452681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The main role of Automatic Generation Control (AGC) is to maintain power grids frequency within specified operating limits. Due to the fact that AGC is the sole automatic feedback control loop between physical and cyber infrastructure in modern power systems and the data required by the AGC system is transferred to a control center through communication links, it can be highly vulnerable to malicious attacks. Therefore, AGC systems should be well-protected against cyberattacks, e.g., False Data Injection (FDI) attacks. In this paper, an intrusion detection and mitigation framework for AGC systems based on a modified Goertzel algorithm is proposed. Compared with the existing intrusion detection and mitigation strategies, the major superiorities of the proposed framework are less computational burden, high accuracy, and rapid detection and mitigation of FDI attacks, which are considered unknown inputs. The proposed framework is validated on a two-area interconnected power systems model and the IEEE 39-bus test system. The dynamic simulation results under different testing conditions verify the applicability and effectiveness of the proposed framework.\",\"PeriodicalId\":100640,\"journal\":{\"name\":\"IEEE Transactions on Industrial Cyber-Physical Systems\",\"volume\":\"2 \",\"pages\":\"412-421\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Industrial Cyber-Physical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10663210/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Industrial Cyber-Physical Systems","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10663210/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

自动发电控制(AGC)的主要作用是将电网频率维持在规定的运行范围内。由于 AGC 是现代电力系统中物理和网络基础设施之间唯一的自动反馈控制回路,而且 AGC 系统所需的数据通过通信链路传输到控制中心,因此极易受到恶意攻击。因此,AGC 系统应针对网络攻击(如虚假数据注入(FDI)攻击)提供良好的保护。本文提出了一种基于改进的 Goertzel 算法的 AGC 系统入侵检测和缓解框架。与现有的入侵检测和缓解策略相比,所提框架的主要优点是计算负担小、准确性高,并能快速检测和缓解被视为未知输入的 FDI 攻击。所提出的框架在两区互联电力系统模型和 IEEE 39 总线测试系统上进行了验证。不同测试条件下的动态仿真结果验证了所提框架的适用性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Intrusion Detection and Mitigation Framework for Automatic Generation Control Systems
The main role of Automatic Generation Control (AGC) is to maintain power grids frequency within specified operating limits. Due to the fact that AGC is the sole automatic feedback control loop between physical and cyber infrastructure in modern power systems and the data required by the AGC system is transferred to a control center through communication links, it can be highly vulnerable to malicious attacks. Therefore, AGC systems should be well-protected against cyberattacks, e.g., False Data Injection (FDI) attacks. In this paper, an intrusion detection and mitigation framework for AGC systems based on a modified Goertzel algorithm is proposed. Compared with the existing intrusion detection and mitigation strategies, the major superiorities of the proposed framework are less computational burden, high accuracy, and rapid detection and mitigation of FDI attacks, which are considered unknown inputs. The proposed framework is validated on a two-area interconnected power systems model and the IEEE 39-bus test system. The dynamic simulation results under different testing conditions verify the applicability and effectiveness of the proposed framework.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信