Stealthy false data injection attacks against extended Kalman filter detection in power grids
文献类型:会议论文
作者 | Liu, Yifa1,2![]() ![]() |
出版日期 | 2021-12 |
会议日期 | 2021.12.10-12 |
会议地点 | Beijing, China |
关键词 | False data injection, state estimation, extended Kalman filter, attack sequence |
DOI | 10.1109/ICCSS53909.2021.9721954 |
英文摘要 | The power grid is a kind of national critical infrastructure directly affiliated to human daily life. Because of the vital functions and potentially significant losses, the power grid becomes an excellent target for many malicious attacks. Due to the special nonlinear measurements, many detection methods do not match the grid very well. The extended Kalman filter based detection is one of the few methods suitable for nonlinear system detection, and therefore can be used in power system to spot malicious attacks. However, the reliability and effectiveness of the extended Kalman filter based detection have not been fully studied and adequately guaranteed. By proposing a two-step false data injection attack strategy, this paper gives a stealthy way to inject false data of increasing magnitude into the power grid, which can eventually cause a certain degree of deviation of the grid state without being detected. In the simulation, the method proposed in this paper caused a voltage deviation of more than 25% before being discovered in the power system. |
会议录 | Proceedings of 2021 8th International Conference on Information, Cybernetics, and Computational Social Systems
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语种 | 英语 |
URL标识 | 查看原文 |
源URL | [http://ir.ia.ac.cn/handle/173211/52242] ![]() |
专题 | 自动化研究所_复杂系统管理与控制国家重点实验室_先进机器人控制团队 多模态人工智能系统全国重点实验室 |
通讯作者 | Cheng, Long |
作者单位 | 1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China |
推荐引用方式 GB/T 7714 | Liu, Yifa,Cheng, Long. Stealthy false data injection attacks against extended Kalman filter detection in power grids[C]. 见:. Beijing, China. 2021.12.10-12. |
入库方式: OAI收割
来源:自动化研究所
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