A Wavelet Neural Network-Based Server Warning System

A server warning system based on wavelet neural network is presented. Wavelet neural network is a kind of neural networks, which combines wavelet theory with neural network theory, that is wavelet function forming neuron, it avoid the problem of nonlinear optimizations, such as local optimization. WNN has fast convergence because of the low correlation of wavelet neuron. In this system,the WNN was trained by using numbered records of system log files in server and the classifier for intrusion detection can be obtained. The experimental result shows that the performance of this system is highly adaptive, the learning speed is fast, and the rate of warning accurate is high, so it is practicable in intrusion detection.