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Machine learning based intelligent system for IP traffic classification.

Author(s)
M. SOHAIB Department of Computer Science and Information Technology, Superior University, Lahore, Pakistan
A. KHALIL Department of Computer Systems Engineering, University of Engineering and Technology Peshawar, Pakistan
K. AHMAD Department of Computer Systems Engineering, University of Engineering and Technology Peshawar, Pakistan
J. KHAN Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
F. IMTIAZ Department of Computer Systems Engineering, University of Engineering and Technology Peshawar, Pakistan
Abstract
As the world has become a global village, internet is considered as preliminary component of each institution, corporation, business as well as an individual. As internet base applications varies on the basis of functionality they provide to the end users, their bandwidth requirements also varies on the basis of Quality of Service (QoS) they provide. Due to the new trend introduced for classification in internet applications like use of dynamic port numbers i.e. P2P applications, classical classification techniques i.e. port based and pay-load based classification are considered inefficient. So to minimize the risk of inefficient IP data classification researchers have adopted Machine Learning (ML) based IP data classification methods. In this paper an effort is made by introducing different classifiers to increase the efficiency of existing Machine Learning techniques for IP data classification.
Publication Details
Page(s) 731-736
DOI DOI not available
Published Journal: Sindh University Research Journal, Volume: 45, Issue: 4, Year: 2013

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