Network Intrusion Detection Method of Power Monitoring System Based on Data Mining

Abstract

At present, the electric power information system has been more widely used. The power sector in the realization of management information at the same time, its security problems are also increasingly severe. It can be said that the security problem of the electric power information has become a hidden danger to the safe and stable operation of the power system. There is a corresponding intrusion problem in the power information network, which affects the stability and security of the power system to a great extent. Aiming at the problem of a long time and low accuracy of network intrusion detection in the power monitoring systems, this paper proposes a method of network intrusion detection in power monitoring systems based on data mining technology. The method can ensure the safe and stable operation of the power monitoring system. This method needs to extract the data characteristics of network intrusion as the initial data set of intrusion detection method, and then apply the clustering partition method to preprocess the data to provide accurate data basis for intrusion detection method, and finally, based on data mining technology, complete the intrusion detection of power monitoring system network. A simulation experiment is designed to test the feasibility and accuracy of the method, and the experimental results show that, compared with the traditional intrusion detection method, the proposed method is faster by about 1.8s, the intrusion detection accuracy is higher by 15.6% for 500 groups of data, and the false alarm rate is lower by 12.3%. It can be proved that the design method in this paper has high efficiency and accuracy, and can provide technical support for the safe operation of the power system.