SVM ensemble for anomaly detection based on rotation forest

Due to the expansion of high-speed Internet access, the need for secure and reliable networks has become more critical. The sophistication of network attacks, as well as their severity, has also increased recently. In this paper, a new intelligent intrusion detection system has been proposed using SVM ensemble. The ensemble was made of two-layer, one is composed by five SVM network decided by winner-take-all, the other is a ensemble network composed of five classifier decided by majority voting. The KDD99 data sets was used to test which achieve a better performance.