考虑负荷数据虚假注入的电力信息物理系统协同攻击模型
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摘要
随着电网信息层与物理层的耦合程度越来越高,配合良好的信息物理协同攻击将对电网造成巨大的威胁。为了更好地保障电网的安全稳定运行,在信息物理高度融合的背景下,提出了一种考虑负荷数据虚假注入的双层协同攻击模型。以广泛应用的基于残差分析的不良数据检测原理为基础,制定网络攻击与物理攻击资源分配约束;以考虑权重的负荷削减期望为损失度量指标,给出了上层攻击者最大化损失和下层防御者最小化损失的具体模型及求解方案;基于修改的IEEE 14节点系统进行了定量分析,得到了不同状态下攻击者的最优攻击方案,为电网防御者在信息物理协同攻击威胁下制定新的防御方案提供参考。
With the increasing high coupling between the cyber layer and the physical layer in the power grid,a well cyber-physical coordinated attack will pose a tremendous threat to the power grid. Under this circumstance,a bi-level coordinated attack model considering the false load data injection is proposed to better ensure the safe and stable operation of the power grid. Based on the widely used residual analysis-based bad data detection principle,the resource allocation constraints of cyber attacks and physical attacks are formulated. The load reduction expectation considering weight is taken as a measure index of loss,and the concrete models and solutions for maximizing the losses of upper attacker and minimizing the losses of lower defenders are given. The quantitative analysis based on the modified IEEE 14-bus system is carried out. The optimal attack scheme of attackers under different states is obtained,which provides a reference for the power grid defenders to formulate the new defensive schemes under the threat of cyberphysical coordinated attacks.
With the increasing high coupling between the cyber layer and the physical layer in the power grid,a well cyber-physical coordinated attack will pose a tremendous threat to the power grid. Under this circumstance,a bi-level coordinated attack model considering the false load data injection is proposed to better ensure the safe and stable operation of the power grid. Based on the widely used residual analysis-based bad data detection principle,the resource allocation constraints of cyber attacks and physical attacks are formulated. The load reduction expectation considering weight is taken as a measure index of loss,and the concrete models and solutions for maximizing the losses of upper attacker and minimizing the losses of lower defenders are given. The quantitative analysis based on the modified IEEE 14-bus system is carried out. The optimal attack scheme of attackers under different states is obtained,which provides a reference for the power grid defenders to formulate the new defensive schemes under the threat of cyberphysical coordinated attacks.
引文
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[17]LIU Y,REITER M K,NING P. False data injection attacks against state estimation in electronic power grids[J]. ACM Transactions on Information and System Security(TISSEC),2011,14(1):1-33.
[18]BI S Z,ZHANG Y J. Graphical methods for Defense against falsedata injection attacks on power system state estimation[J]. IEEE Transactions on Smart Grid,2014,5(3):1216-1227.
[19]YINGMENG X,WANG L F,YU D,et al. Coordinated attacks against power grids:load redistribution attack coordinating with generator and line attacks[C]∥2015 IEEE Power&Energy Society General Meeting. Denver,CO,USA:IEEE,2015:1-5.
[20]AL MANNAI W I,LEWIS T G. A general defender-attacker risk model for networks[J]. The Journal of Risk Finance,2008,9(3):244-261.
[2]李中伟,佟为明,金显吉.智能电网信息安全防御体系与信息安全测试系统构建乌克兰和以色列国家电网遭受网络攻击事件的思考与启示[J].电力系统自动化,2016,40(8):147-151.LI Zhongwei,TONG Weiming,JIN Xianji. Construction of cyber security defense hierarchy and cyber security testing system of smart grid:thinking and enlightenment for network attack events to national power grid of Ukraine and Israel[J]. Automation of Electric Power Systems,2016,40(8):147-151.
[3]陈柯任,文福拴,赵俊华,等.考虑物理-信息虚拟连接的电力信息物理融合系统的脆弱性评估[J].电力自动化设备,2017,37(12):67-72,79.CHEN Keren,WEN Fushuan,ZHAO Junhua,et al. Vulnerability assessment of cyber-physical power system considering virtual cyberphysical connections[J]. Electric Power Automation Equipment,2017,37(12):67-72,79.
[4]金波,肖先勇,李长松.基于一、二次系统交互关系的电网连锁故障演化机制分析[J].电力自动化设备,2017,37(1):169-175.JIN Bo,XIAO Xianyong,LI Changsong. Analysis of cascading failure evolution based on interaction between primary and secondary systems[J]. Electric Power Automation Equipment,2017,37(1):169-175.
[5]刘取,刘宪林. 21世纪电力系统的先进技术[J].电力自动化设备,2010,30(7):1-13,29.LIU Qu,LIU Xianlin. Advanced technologies of power system in the21st century[J]. Electric Power Automation Equipment,2010,30(7):1-13,29.
[6]王宇飞,高昆仑,赵婷,等.基于改进攻击图的电力信息物理系统跨空间连锁故障危害评估[J].中国电机工程学报,2016,36(6):1490-1499.WANG Yufei,GAO Kunlun,ZHAO Ting,et al. Assessing the harmfulness of cascading failures across space in electric cyber-physical system based on improved attack graph[J]. Proceedings of the CSEE,2016,36(6):1490-1499.
[7]韩宇奇,郭创新,朱炳铨,等.基于改进渗流理论的信息物理融合电力系统连锁故障模型[J].电力系统自动化,2016,40(17):30-37.HAN Yuqi,GUO Chuangxin,ZHU Bingquan,et al. Model cascading failures in cyber physical power system based on improved percolation theory[J]. Automation of Electric Power Systems,2016,40(17):30-37.
[8]汪勋婷,王波.考虑信息物理融合的电网脆弱社团评估方法[J].电力自动化设备,2017,37(12):43-51.WANG Xunting,WANG Bo. Assessment method of vulnerable communities in power grid considering cyber-physical integration[J].Electric Power Automation Equipment,2017,37(12):43-51.
[9]石立宝,简洲.基于动态攻防博弈的电力信息物理融合系统脆弱性评估[J].电力系统自动化,2016,40(17):99-105.SHI Libao,JIAN Zhou. Vulnerability assessment of cyber physical power system based on dynamic attack-defense game model[J].Automation of Electric Power Systems,2016,40(17):99-105.
[10]LI Z Y,SHAHIDEHPOUR M,ALABDULWAHAB A,et al. Bilevel model for analyzing coordinated cyber-physical attacks on power systems[J]. IEEE Transactions on Smart Grid,2016,7(5):2260-2272.
[11]LI Z Y,SHAHIDEHPOUR M,ALABDULWAHAB A,et al. Analyzing locally coordinated cyber-physical attacks for undetectable line outages[J]. IEEE Transactions on Smart Grid,2018,9(1):35-47.
[12]DENG R L,ZHUANG P,LIANG H. CCPA:coordinated cyber-physical attacks and countermeasures in smart grid[J]. IEEE Transactions on Smart Grid,2017,8(5):2420-2430.
[13]YUAN Y L,LI Z Y,REN K. Modeling load redistribution attacks in power systems[J]. IEEE Transactions on Smart Grid,2011,2(2):382-390.
[14]YUAN Y L,LI Z Y,REN K. Quantitative analysis of load redistribution attacks in power systems[J]. IEEE Transactions on Parallel and Distributed Systems,2012,23(9):1731-1738.
[15]LIU X,BAO Z,LU D,et al. Modeling of local false data injection attacks with reduced network information[J]. IEEE Transactions on Smart Grid,2015,6(4):1686-1696.
[16]XIANG Y M,DING Z L,ZHANG Y C,et al. Power system reliability evaluation considering load redistribution attacks[J]. IEEE Transactions on Smart Grid,2016,8(2):889-901.
[17]LIU Y,REITER M K,NING P. False data injection attacks against state estimation in electronic power grids[J]. ACM Transactions on Information and System Security(TISSEC),2011,14(1):1-33.
[18]BI S Z,ZHANG Y J. Graphical methods for Defense against falsedata injection attacks on power system state estimation[J]. IEEE Transactions on Smart Grid,2014,5(3):1216-1227.
[19]YINGMENG X,WANG L F,YU D,et al. Coordinated attacks against power grids:load redistribution attack coordinating with generator and line attacks[C]∥2015 IEEE Power&Energy Society General Meeting. Denver,CO,USA:IEEE,2015:1-5.
[20]AL MANNAI W I,LEWIS T G. A general defender-attacker risk model for networks[J]. The Journal of Risk Finance,2008,9(3):244-261.