期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2014
卷号：3
期号：10
页码：8964-8971
出版社：IJECS
摘要：Internet traffic classification is a fundamental technology for modern network security such as quality of service(QoS) control. It is useful to tackle a number of network security problems including lawful interception and intrusiondetection. There is an increasing demand on the development of modern traffic classification techniques due to thedevelopment of different application. In this work, Internet traffic is carried out by using the supervised classificationtechniques namely the Neural Network such as Multilayer perceptron (MLP) and Radial base function (RBF) and HybridAggregated Classifier. The task involved in this work is IP packet capturing, Preprocessing, Flow container construction (Ifthe flows observed in a certain period of time share the same destination IP, port, and transport layer protocol, they aredetermined as correlated flows and modeled as “Flow Container”), separating low density and high density flow, featureextraction and classification. The accuracy of the classifier Hybrid aggregated classification is better than Neural Network.
