Research On Improvement And Application Of Intrusion Detection Method For Liaoning Smart Grid

In this study,the smart grid system in Liaoning province is taken as the research object,and the existing security problems are analyzed.Then the intrusion detection system is formulated and the algorithm is improved.The main use is the rule description method compatible with R-NNIDS system and Snort,which can simplify the description of aggressive data packets in the network,and reduce the amount of data.The SVM model is established,and the smart grid intrusion detection method is improved based on the neural network,and the detection is performed.The false alarm rate and the false negative rate of the detection system are reduced as a whole,and the data volume is reduced,the work convenience is improved,the cost is reduced,and Good service for the development of smart grid management.In the specific research process,the key issues to be solved are:how to innovate intrusion detection methods,how to improve the design of intrusion detection systems,how to accurately identify intrusion behaviors and enhance the detection capability for new intrusion behaviors.Through practical research,the following conclusions are drawn:The whole intrusion detection model is designed using SVM.The method is secondary decomposition method,SOM method and LM method,and it is improved.The KPCA algorithm is used to set the neural network classifier flag.For KPCAINN,the classifier flag of ICA method is used.Set to ICAINN.The test results are relatively good and practical.The R-NNIDS system is designed reasonably and some new intrusion behaviors can be found.In addition,the risks faced by the smart grid in Liaoning Province are that the hardware and communication facilities of the computer system are vulnerable to natural environment,natural disasters and man-made physical damage,and the software and data of the computer system are vulnerable to attacks such as illegal theft,duplication,tampering and destruction.Different sources of risks are different,and in the process of practical work,it is necessary to strengthen the management of these risks.