Coarse-Grained Classification Of P2p Network Traffic Using Filter/Wrapper Features Selection
||International Journal of P2P Network Trends and Technology (IJPTT)||
|© 2019 by IJPTT Journal|
|Year of Publication : 2019|
|Authors : Haitam A. Jamil, Bushra M. Ali, Ahmed E. Osman, Hind G. Abdelrahim|
|DOI : 10.14445/22492615/IJPTT-V9I5P402|
MLA Style: Haitam A. Jamil, Bushra M. Ali, Ahmed E. Osman, Hind G. Abdelrahim "Coarse-Grained Classification Of P2p Network Traffic Using Filter/Wrapper Features Selection" International Journal of P2P Network Trends and Technology 9.5 (2019): 13-16.
APA Style:Haitam A. Jamil, Bushra M. Ali, Ahmed E. Osman, Hind G. Abdelrahim(2019). Coarse-Grained Classification Of P2p Network Traffic Using Filter/Wrapper Features Selection. International Journal of P2P Network Trends and Technology, 9(5), 13-16.
Classifying network traffic applications is needed for network security and controlling. The emergence of new Internet applications with the use of encryption techniques, gains significant attention in the last period of time. However, the problem of using huge features requires longer processing time as well as low classification accuracy. Therefore, feature selections have a significant impact on classification performance. In this paper, we propose Filter/Wrapper feature selection methods for flow-based Internet traffic Classification using Machine Learning techniques. The evaluation has been carried out through experiments on the traffic traces downloaded from different shared resources. The experiments demonstrate our approach can greatly improve the computational performance.
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Coarse-grained classification; features selection; wrapper approach; filter method.