智能电网中的虚假数据注入攻击检测方法研究
|
摘要
针对当前FDIAs篡改电网数据,从而绕过传统的数据检测机制,最终导致控制中心根据这种虚假数据注入做出错误的判断,以此导致整个智能电网出现故障的问题,提出一种基于聚类算法与状态预测检测法的FDIAs检测技术。为实现FDIAs攻击检测,文章首先对虚假数据注入攻击的原理进行分析,以此为后续的攻击检测提供理论基础;然后结合目前的攻击检测方法,提出节点电压稳定性的指标检测方法。通过构建NVSI与FDIAs之间的关系,结合NVSI值对FDIAs进行初步量化,以此对脆弱节点进行初步辨识,然后采用聚类算法对脆弱性的节点进行分类,并划分节点等级;最后通过状态预测检测法完成对虚假FDIAs的检测。通过仿真,并以IEEE14-bus标准测试系统作为基础,对上述的方法进行了验证,表明了本文方法的可行性。
Aiming at the problem of current FDIAs tamper with power grid data and bypass the traditional data detection mechanism,the control center makes wrong judgment based on this false data injection,which leads to the fault of the whole smart grid,a FDIAs detection technology based on clustering algorithm and state prediction detection method is proposed.In order to implement FDIAs attack detection,the principle of false data injection attack is analyed which provides a theoretical basis for subsequent attack detection.Then,combined with the current attack detection methods,the index detection method of node voltage stability is proposed.By constructing the relationship between NVSI and FDIAs,and combining NVSI value to preliminarily quantify FDIAs,the fragile nodes are identified preliminarily.Then the fragile nodes are classified and classified by clustering algorithm.Finally,the false FDIAs are detected by state prediction detection method.Finally,through simulation and based on IEEE14-bus Standard Test system,the above methods are verified,and the feasibility of this method is verified.
Aiming at the problem of current FDIAs tamper with power grid data and bypass the traditional data detection mechanism,the control center makes wrong judgment based on this false data injection,which leads to the fault of the whole smart grid,a FDIAs detection technology based on clustering algorithm and state prediction detection method is proposed.In order to implement FDIAs attack detection,the principle of false data injection attack is analyed which provides a theoretical basis for subsequent attack detection.Then,combined with the current attack detection methods,the index detection method of node voltage stability is proposed.By constructing the relationship between NVSI and FDIAs,and combining NVSI value to preliminarily quantify FDIAs,the fragile nodes are identified preliminarily.Then the fragile nodes are classified and classified by clustering algorithm.Finally,the false FDIAs are detected by state prediction detection method.Finally,through simulation and based on IEEE14-bus Standard Test system,the above methods are verified,and the feasibility of this method is verified.
引文
[1] 赵俊华,梁高琪,文福拴,等.乌克兰事件的启示:防范针对电网的虚假数据注入攻击[J].电力系统自动化,2016,(40)58107:149-151.
[2] 赵俊华,梁高琪,文福拴,等.乌克兰事件的启示:防范针对电网的虚假数据注入攻击[J].电力系统自动化,2016,40(07):149-151.
[3] 汤奕,陈倩,李梦雅,等.电力信息物理融合系统环境中的网络攻击研究综述[J].电力系统自动化,2016,40(17):59-69.
[4] 田继伟,王布宏,尚福特.基于鲁棒主成分分析的智能电网虚假数据注入攻击[J].计算机应用,2017,(37)32307:1943-1947+1971.
[5] 田继伟,王布宏,尚福特,等.基于数据驱动的稀疏虚假数据注入攻击[J].电力自动化设备,2017,(37)28412:52-59.
[6] 何耀,张维锡,粟秋成,等.智能电网虚假数据攻击的非线性稀疏建模研究[J].电力信息与通信技术,2017,(15)17010:126-131.
[7] 舒隽,郭志锋,韩冰.电网虚假数据注入攻击的非线性分析模型[J].华北电力大学学报(自然科学版),2018,(45)19202:75-81.
[8] 朱杰,张葛祥,王涛,等.电力系统状态估计欺诈性数据攻击及防御综述[J].电网技术,2016,40(08):2406-2415.
[9] 许婧.考虑保护隐藏故障的复杂电力系统连锁故障分析研究[D].中国电力科学研究院,2011.
[10] 曹燕华,章志明,余敏.基于信任管理机制的无线传感器网络虚假数据过滤方案[J].计算机应用,2014,(34)28606:1567-1572.
[11] 李青芯,孙宏斌,盛同天,等.变电站状态估计中互感器虚假数据注入攻击分析[J].电力系统自动化,2016,(40)59117:79-86.
[12] 蒋荣辉.电力调度自动化系统数据注入攻击的保护策略[J].自动化应用,2018,05:83-85.
[13] 罗小元,朱鸣皋,王新宇,等.基于自适应卡尔曼滤波器的智能电网隐蔽假数据攻击检测[J].信息与控制,2018,(4701):16-21.
[14] 李文琴,范会联,文俊浩.一种抵抗智能电网数据注入攻击的认证密钥机制[J].电子技术应用,2015,(41)45012:109-112.
[15] 刘俊辉,张斌.在智能电网中使用SVM方法检测隐形假数据注入[J].电子世界,2018,(54208):195-196.
[16] 汤奕,陈倩,李梦雅,等.电力信息物理融合系统环境中的网络攻击研究综述[J].电力系统自动化,2016,(40)59117:59-69.
[2] 赵俊华,梁高琪,文福拴,等.乌克兰事件的启示:防范针对电网的虚假数据注入攻击[J].电力系统自动化,2016,40(07):149-151.
[3] 汤奕,陈倩,李梦雅,等.电力信息物理融合系统环境中的网络攻击研究综述[J].电力系统自动化,2016,40(17):59-69.
[4] 田继伟,王布宏,尚福特.基于鲁棒主成分分析的智能电网虚假数据注入攻击[J].计算机应用,2017,(37)32307:1943-1947+1971.
[5] 田继伟,王布宏,尚福特,等.基于数据驱动的稀疏虚假数据注入攻击[J].电力自动化设备,2017,(37)28412:52-59.
[6] 何耀,张维锡,粟秋成,等.智能电网虚假数据攻击的非线性稀疏建模研究[J].电力信息与通信技术,2017,(15)17010:126-131.
[7] 舒隽,郭志锋,韩冰.电网虚假数据注入攻击的非线性分析模型[J].华北电力大学学报(自然科学版),2018,(45)19202:75-81.
[8] 朱杰,张葛祥,王涛,等.电力系统状态估计欺诈性数据攻击及防御综述[J].电网技术,2016,40(08):2406-2415.
[9] 许婧.考虑保护隐藏故障的复杂电力系统连锁故障分析研究[D].中国电力科学研究院,2011.
[10] 曹燕华,章志明,余敏.基于信任管理机制的无线传感器网络虚假数据过滤方案[J].计算机应用,2014,(34)28606:1567-1572.
[11] 李青芯,孙宏斌,盛同天,等.变电站状态估计中互感器虚假数据注入攻击分析[J].电力系统自动化,2016,(40)59117:79-86.
[12] 蒋荣辉.电力调度自动化系统数据注入攻击的保护策略[J].自动化应用,2018,05:83-85.
[13] 罗小元,朱鸣皋,王新宇,等.基于自适应卡尔曼滤波器的智能电网隐蔽假数据攻击检测[J].信息与控制,2018,(4701):16-21.
[14] 李文琴,范会联,文俊浩.一种抵抗智能电网数据注入攻击的认证密钥机制[J].电子技术应用,2015,(41)45012:109-112.
[15] 刘俊辉,张斌.在智能电网中使用SVM方法检测隐形假数据注入[J].电子世界,2018,(54208):195-196.
[16] 汤奕,陈倩,李梦雅,等.电力信息物理融合系统环境中的网络攻击研究综述[J].电力系统自动化,2016,(40)59117:59-69.