A Wavelet Transform Based Support Vector Machine Ensemble Algorithm and Its Application in Network Intrusion Detection

Traditional network intrusion detection algorithms are time consuming due to the existence of redundant attributes. In order to improve the efficiency of network intrusion detection, in this paper, we propose a wavelet transform based support vector machine ensemble algorithm. Firstly, we use wavelet transform to remove the redundant attributes from the original dataset. Then we train a support vector machine ensemble on the simplified dataset. As the wavelet transform in this algorithm can effectively remove the redundant attributes, the proposed algorithm is with high efficiency. Simulation experiments on KDD CUP 99 data set show that the proposed algorithm has good intrusion detection performance.