| The main expectation of smart grid is to distribute the control and automation process in the whole power grid,so as to achieve efficient and reliable two-way power flow.This is achieved by integrating information and communication technologies(ICT)into the power grid,making it a kind of network physical system(CPS).Smart grid brings revolutionary changes to our society,economy and environment with its promising technology.Companies of all sizes have high hopes for the emerging market of smart grid technology,and have taken the lead in launching various power equipment.However,the security problem is also emerging in this upsurge.With the introduction of various ICT components,the fragile security of smart grid has also been greatly threatened.The false data injection(FDI)attack is a highly covert attack,which has attracted the attention of smart grid security researchers since it was proposed by Yao Liu in 2009.The attacker uses the acquired power system configuration knowledge to launch an attack that can avoid the detection of bad data,inject false data into the state variables,and make the state results wrong,which leads to the wrong decision of the supervisory control and data acquisition(SCADA)system.Therefore,the in-depth study of FDI attacks is of great significance to ensure the safe and stable operation of the power grid.Therefore,this paper focuses on the attack methods and detection methods of FDI attacks.The specific contents are as follows:1.Research on the method of FDI attack: This paper proposes a method of exchange FDI attack based on time nodes when the local topology information is mastered.The attacker can launch the attack with the highest success rate and the strongest destructiveness when he has a complete grasp of the power system topology.However,due to the protection of the power grid to the control center and the bad environment of the remote terminal unit(RTU)unit distribution,it is difficult for the attacker to obtain the complete system topology information.Therefore,in the third chapter,we propose a method of FDI attack under the condition of mastering the local information of system topology.And because people's daily life changes,the power load of different time nodes in a day also changes,so that different time nodes need different number of instruments to attack.Therefore,this paper proposes a false data injection attack method based on time nodes,aiming to find an optimal attack time node to launch the attack.Because the number of instruments that need to be destroyed by different routes in different time nodes is different,and the more attacks,the more likely the instrument will be found,the attacker will find a time node with the least number of instruments that need to be destroyed to launch FDI attacks as the optimal attack strategy.2.Research on FDI detection method: This paper proposes a false data injection attack detection method combining PCA and SVM Because the measurement data in the power grid has high dimensional correlation,we can use the principal component analysis method to reduce the dimension of measurement data.The principal component analysis method is an effective dimension reduction method,which can maximize the projection variance after dimension reduction,indirectly maximize the difference between normal data and abnormal data,so as to improve the accuracy of detection.Support vector machine(SVM)is a commonly used classification method in machine learning.Its basic idea is to find an optimal partition hyperplane based on the training set in the sample space and separate different categories.It is very fast to classify the new data,only to judge which side of the boundary line the coordinates are on.Therefore,this paper can effectively detect FDI and reduce the training and testing time by combining PCA and SVM.3.The attack method and detection method proposed in this paper are tested on IEEE 14 bus and IEEE 118 bus standard test system respectively,and the effectiveness of the proposed method is verified by simulation results. |
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