The paper is devoted to identification and classification of network traffic connections by
various hybridization schemes with the goal of efficient network attack detection. For this
purpose the combination of different methods of computational intelligence is used, namely
neural networks, immune systems, neuro-fuzzy classifiers and support vector machines. To
increase the speed of processing of input vectors it is proposed to apply the method of
principal components. A distinctive feature and advantage of the approach suggested is a …