A network intrusion detection method based on combined model

Abstract

In order to make the detecting rate faster and improve the accuracy of network intrusion detection, this paper ameliorated a network intrusion detection method which was based on combining support vector machines and LVQ (Learning vector quantization) neural network algorithm. The method combines the popularizing capability of SVM and the learning capability of LVQ neural network. It overcame the shortcomings of traditional neural network algorithm, such as the slower learning speed and the larger possibility of falling into local minimum. Examples proved that this combined model had faster speed and higher rate of accuracy . What is more, it better resolved a series of detecting problems, such as nonlinearity, small-sample, high-dimension and local minimum.