Converter-Based Moving Target Defense Against Deception Attacks in DC Microgrids

欺骗 MATLAB语言 计算机科学 电压 功率(物理) 控制(管理) 理论(学习稳定性) 控制理论(社会学) 计算机安全 电子工程 工程类 电气工程 人工智能 心理学 机器学习 物理 操作系统 社会心理学 量子力学
作者
Mengxiang Liu,Chengcheng Zhao,Zhenyong Zhang,Ruilong Deng,Peng Cheng,Jiming Chen
出处
期刊:IEEE Transactions on Smart Grid [Institute of Electrical and Electronics Engineers]
卷期号:13 (5): 3984-3996 被引量:63
标识
DOI:10.1109/tsg.2021.3129195
摘要

With the rapid development of information and communications technology in DC microgrids (DCmGs), the deception attacks, which typically include false data injection and replay attacks, have been widely recognized as a significant threat. However, existing literature ignores the possibility of the intelligent attacker, who could launch deception attacks once obtaining necessary information by exploiting zero-day vulnerabilities or bribing insiders, to affect the system in an unforeseeable manner. In this paper, based on the observation that the primary control law of the power converter device in DCmGs is usually programmable, we propose a novel converter-based moving target defense (CMTD) strategy by proactively perturbing the primary control gains to defend against deception attacks. First, we study the impact of perturbing the primary control gains on the voltage stability in DCmGs and provide explicit conditions for the perturbation magnitude and frequency under which the voltage stability can be ensured. Then, we investigate the improved detectability against deception attacks under CMTD and present sufficient conditions under which these attacks can be detected. Finally, we conduct extensive MATLAB SIMULINK/PLECS based simulations and systematic hardware-in-the-loop based experiments to validate the effectiveness of CMTD.
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