Network Intrusion Detection Based on Lightning Search Algorithm Optimized Extreme Learning Machine
Chunzhi Wang, Wencheng Cai, Zhiwei Ye, Lingyu Yan, Pan Wu, Yichao Wang · 2018
In order to guarantee the security of the network, a lightning search algorithm optimized extreme learning machine(LSA-ELM) method is proposed in this paper, aiming at the problem of parameter optimization in the process of network intrusion detection by extreme learning machine. First, the parameters of extreme learning machine are coded as the discharge projectile position, and the total weighted error is taken as the fitness value. Then the optimal parameters of the extreme learning machine are found by simulating the lightning discharge behavior, and a network intrusion detection classifier is established. Finally, The KDD99 data set is used for simulation experiments on the MATLAB 2015a platform. The results show that LSA-ELM improves the accuracy of network intrusion detection and meets the requirements of online intrusion detection.