  In this paper, we apply a fusion machine learning method to construct an
automatic intrusion detection system. Concretely, we employ the orthogonal
variance decomposition technique to identify the relevant features in network
traffic data. The selected features are used to build a deep neural network for
intrusion detection. The proposed algorithm achieves 100% detection accuracy in
identifying DDoS attacks. The test results indicate a great potential of the
proposed method.
