基于蠕虫传播和FDI的电力信息物理协同攻击策略  

The Coordinated Cyber Physical Power Attack Strategy Based on Worm Propagation and False Data Injection

作　　者：冯晓萌 孙秋野[1] 王冰玉[1] 高嘉文 FENG Xiao-Meng;SUN Qiu-Ye;WANG Bing-Yu;GAO Jia-Wen(College of Information Science and Engineering,Northeastern University,Shenyang 110819)

机构地区：[1]东北大学信息科学与工程学院,沈阳110819

出　　处：《自动化学报》2022年第10期2429-2441,共13页Acta Automatica Sinica

基　　金：国家自然科学基金重点项目(61433004);国家自然科学基金(61573094)资助。

摘　　要：随着信息技术与现代电力系统的结合日趋紧密,通信系统异常和网络攻击均可能影响到电力系统的安全稳定运行.为了研究工控蠕虫病毒对电网带来的安全隐患,本文首次建立了基于马尔科夫决策过程(Markov decision process,MDP)的电力信息物理系统跨空间协同攻击模型,该模型同时考虑通信设备漏洞被利用的难易程度为代价以及对电力网络的破坏程度为收益两方面因素,能够更有效地识别系统潜在风险.其次,采用Q学习算法求解在该模型下的最优攻击策略,并依据电力系统状态估计的误差值来评定该攻击行为对电力系统造成的破坏程度.最后,本文在通信8节点-电力14节点的耦合系统上进行联合仿真,对比结果表明相较单一攻击方式,协同攻击对电网的破坏程度更大.与传统的不考虑通信网络的电力层攻击研究相比,本模型辨识出的薄弱节点也考虑了信息层的关键节点的影响,对防御资源的分配有指导作用.With the deep integration of information technologies in modern power systems, cyber system anomalies and network attacks can threaten the safety and stability of power system operation. To study the security risks of the power system caused by the latest industrial control worm, a coordinated cyber-physical power attack model based on the Markov decision process(MDP) is proposed in this paper. Then, the Q-learning algorithm is adopted to search for the optimal attack strategy in the proposed model, and the error of state estimation result induced by the attacks is devised to quantify the potential physical influences-attack benefits. Eventually, numerical joint simulation experiments are conducted on the 8CYBER_NODE-14BUS coupling test system, and the results show that the coordinated attack model proposed in this paper is more destructive. Compared with the traditional isolated physical attack without considering the cyber network, the identified weak nodes can also consider the influence of the cyber devices and guide the allocation of defense resources.

关 键 词：SIR蠕虫模型 虚假数据注入 信息物理联合仿真 电力系统状态估计 Q学习 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术] TM73[自动化与计算机技术—计算机科学与技术]