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Focus on Deep Neural Network based malicious and normal computer NetworkTraffic classification. (such as attacks, phishing, any other illegal activityand normal traffic identification). In this paper, the main idea is to review,existed Neural Network based network traffic classification. Which indicatesintrusion activity classification and detection. It is very important toclassify network traffic to safeguard any system, connected to computernetwork. There are a variety of NN architecture for it, with different rate ofaccuracy. On this paper we will do relative compression among them. IndexTerms-Computer Network, Network traffic, Packet, Intrusion, DOS(Denial-of-service), unauthorized access, IDS (Intrusion Detection System), IPS(Intrusion Prevention Systems), R2L (Remote to Local Attack), Probing, U2R(User to Root Attack), DNN (Deep Neural Network), CRNN (Convolutional RecurrentNeural Network), RPROP (Resilient propagation).

A review on Deep Neural Network for Computer Network Traffic Classification