关键词: 主成分分析, 入侵检测, 极限学习机, BP 神经网络

Abstract: Because the intrusion detection based on traditional BP (Back Propagation) neural network has
deficiency in the convergence speed and detection rate, a method based on ELM(Extreme Learning Machine)
using PCA(Principal Component Analysis) is proposed. We use PCA to reduce the dimension of the extracted
eigenmatrix and use ELM to detect four types of common attacks. The experimental results show that the accuracy
of the proposed method can reach 98. 337 5%, and the detection time is as fast as 1. 851 7 s. This method also
improves the detection rate and precision, and reduces the false positive rate and false negative rate. The
proposed method achieves the improvement of these six criterions.

Key words: intrusion detection, back propagation neural network, extreme learning machine(ELM), principal component analysis(PCA)