Coordinated Topology Attacks in Smart Grid Using Deep Reinforcement Learning

被引:44
作者
Wang, Zhenhua [1 ]
He, Haibo [1 ]
Wan, Zhiqiang [1 ]
Sun, Yan [1 ]
机构
[1] Univ Rhode Isl, Dept Elect Comp & Biomed Engn, Kingston, RI 02881 USA
关键词
Topology; Transmission line measurements; Power transmission lines; Power measurement; Biomedical measurement; Voltage measurement; Coordinated topology attacks; deep reinforcement learning; load redistribution (LR) attacks; LINE OUTAGE; CYBER; COUNTERMEASURES; MODEL;
D O I
10.1109/TII.2020.2994977
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, we investigate the coordinated topology attacks in smart grid, which combine a physical topology attack and a cyber-topology attack. The physical attack first trips a transmission line. In order to deceive the control center, the attacker masks the outage signal of the tripped line in the cyber layer and then creates a fake outage signal for another transmission line. The goal of coordinated topology attacks is to overload a critical line (different from the physical tripped line and the fake outage line) by misleading the control center into making improper dispatch. In order to determine the attack strategy, we propose a deep-reinforcement-learning-based method to identify the physical tripped line and the fake outage line. Besides, in order to block the outage signal of the tripped line and create the fake outage signal with limited attack resources, we propose a deep-reinforcement-learning-based approach to determine the minimal attack resources. Numerical simulations verify the effectiveness of the proposed method.
引用
收藏
页码:1407 / 1415
页数:9
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