Network intrusion clustering method based on improved LDA and CNN
Tan Lizhi · Computer Engineering and Applications Journal · 2013
A hybrid method of improved Linear Discriminant Analysis(LDA)and Center-based Nearest Neighbor(CNN)classifier for clustering of network intrusions is proposed.The improved LDA is employed to reduce the dimensions of sample vector,and then the center-based nearest neighbor classifier is used to cluster for the data of network intrusions.The proposed algorithm not only reduces the clustering time of the algorithm,but also improves the clustering ability.Experimental results indicate that the proposed algorithm obtains higher clustering capability contrast to other models at a higher detection rate and a lower false alarm rate.