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Reseach Article

State of the Art Review of Network Traffic Classification based on Machine Learning Approach

Published on May 2013 by Pallavi Singhal, Rajeev Mathur, Himani Vyas
International Conference on Recent Trends in Engineering and Technology 2013
Foundation of Computer Science USA
ICRTET - Number 1
May 2013
Authors: Pallavi Singhal, Rajeev Mathur, Himani Vyas
384dfc62-1bb3-453d-bb2c-e88ac640c2d3

Pallavi Singhal, Rajeev Mathur, Himani Vyas . State of the Art Review of Network Traffic Classification based on Machine Learning Approach. International Conference on Recent Trends in Engineering and Technology 2013. ICRTET, 1 (May 2013), 12-16.

@article{
author = { Pallavi Singhal, Rajeev Mathur, Himani Vyas },
title = { State of the Art Review of Network Traffic Classification based on Machine Learning Approach },
journal = { International Conference on Recent Trends in Engineering and Technology 2013 },
issue_date = { May 2013 },
volume = { ICRTET },
number = { 1 },
month = { May },
year = { 2013 },
issn = 0975-8887,
pages = { 12-16 },
numpages = 5,
url = { /proceedings/icrtet/number1/11760-1307/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference on Recent Trends in Engineering and Technology 2013
%A Pallavi Singhal
%A Rajeev Mathur
%A Himani Vyas
%T State of the Art Review of Network Traffic Classification based on Machine Learning Approach
%J International Conference on Recent Trends in Engineering and Technology 2013
%@ 0975-8887
%V ICRTET
%N 1
%P 12-16
%D 2013
%I International Journal of Computer Applications
Abstract

Network traffic classification is extensively required mainly for many network management tasks such as flow prioritization, traffic shaping/policing, and diagnostic monitoring. Similar to network management tasks, many network engineering problems such as workload characterization and modeling, capacity planning, and route provisioning also benefit from accurate identification of network traffic . This paper presents review on all the work done related to Network Traffic Management since 1993 to 2013 in various fields like artificial intelligence, neural network, ATM and wireless networks.

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Index Terms

Computer Science
Information Sciences

Keywords

Network Traffic Supervised Unsupervised Learning Semi-supervised Clustering Classification Machine Learning