Power Grid Risky IP Identification Algorithm Based on Hybrid Genetic Ensemble Learning

Abstract

In the increasingly severe situation of network security, the blocking of external IP based on regional characteristics, which requires manpower to judge and operate, is becoming inadequate. Aiming at the practical problems existing in the network security defense of power enterprises, this paper proposed a risky IP identification algorithm based on hybrid genetic ensemble learning. The algorithm comprehensively used the improved genetic algorithm and the selective ensemble algorithm to establish a risky IP identification and prediction model. At the same time, A variety of network security information data were widely used to test the algorithm. The results show that the ensemble learning algorithm based on hybrid genetic can effectively identify risky IP and has higher recognition accuracy.