| Title | Research on Network Intrusion Detection Method of Power System Based on Random Forest Algorithm |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | ZHU, Guowei, YUAN, Hui, ZHUANG, Yan, GUO, Yue, ZHANG, Xianfei, QIU, Shuang |
| Conference Name | 2021 13th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA) |
| Date Published | jan |
| Keywords | Clustering algorithms, composability, Data models, Image edge detection, Intrusion detection, Mechatronics, Metrics, network intrusion, network intrusion detection, Power measurement, power system, Power systems, pubcrawl, random forest algorithm, resilience, Resiliency |
| Abstract | Aiming at the problem of low detection accuracy in traditional power system network intrusion detection methods, in order to improve the performance of power system network intrusion detection, a power system network intrusion detection method based on random forest algorithm is proposed. Firstly, the power system network intrusion sub sample is selected to construct the random forest decision tree. The random forest model is optimized by using the edge function. The accuracy of the vector is judged by the minimum state vector of the power system network, and the measurement residual of the power system network attack is calculated. Finally, the power system network intrusion data set is clustered by Gaussian mixture clustering Through the design of power system network intrusion detection process, the power system network intrusion detection is realized. The experimental results show that the power system network intrusion detection method based on random forest algorithm has high network intrusion detection performance. |
| DOI | 10.1109/ICMTMA52658.2021.00087 |
| Citation Key | zhu_research_2021 |
Research on Network Intrusion Detection Method of Power System Based on Random Forest Algorithm