Some aspects of neural network approach for intrusion detection

Intrusion detection techniques are of great importance for computer network protecting because of increasing the number of remote attack using TCP/IP protocols. There exist a number of intrusion detection systems, which are based on different approaches for anomalous behavior detection. This paper focuses on applying neural networks for intrusion detection and recognition. It is based on nonlinear PCA network and multilayer perceptron. The 1999 KDD Cup data set is used for F training and testing neural networks. The results of experiments are discussed in the paper.