Learning vector quantization neural network method for network intrusion detection
Degang Yang, Guo Chen, Hui Wang, Xiaofeng Liao · Wuhan University Journal of Natural Sciences · 2007
A new intrusion detection method based on learning vector quantization (LVQ) with low overhead and high efficiency is presented. The computer vision system employs LVQ neural networks as classifier to recognize intrusion. The recognition process includes three stages: 1 feature selection and data normalization processing; 2 learning the training data selected from the feature data set; 3 identifying the intrusion and generating the result report of machine condition classification. Experimental results show that the proposed method is promising in terms of detection accuracy, computational expense and implementation for intrusion detection.