False Data Injection Attack Detection of Cyber-physical Power System Based on ASRUKF and IMC Algorithms
To solve the problem of low accuracy of false data injection attack(FDIA)detection in traditional power information physical system,a new FDIA detection method based on adaptive Sage-Husa unscented Kalman filter(ASRUFK)and improved Markov chain(IMC)prediction algorithm is proposed.Firstly,an improved Markov chain(IMC)prediction algorithm is proposed by adding random interpolation to adjust the state interval.Secondly,ASRUKF and IMC prediction algorithms are used to estimate the state of the data to be measured in the system,and random variables are constructed according to the deviation values of the state estimation results of the two prediction algorithms.Box-Cox is used to convert random variables into variables with normal distribution.Finally,the FDIA detection of the power information physical system is realized through bilateral hypothesis testing.The validity and correctness of the proposed method are verified in IEEE-14 node and IEEE-30 node systems.
power cyber-physical systemfalse data injection attackimproved Markov chain prediction algorithmBox-Cox transformationattack detection
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