Article: A study on flow based classification models using machine learning techniques Journal: International Journal of Intelligent Systems Technologies and Applications (IJISTA) 2018 Vol.17 No.4 pp.467 - 482 Abstract: Network traffic management facing a lot of challenges in the recent years because of the continuous and fast development in network scale, number of consumers and type of known and unknown applications over the network. Traffic classification is a key factor for providing the quality of network services (QoS), handling the delay and congestion during the transmission. In the field of network traffic classification, Machine learning algorithms are playing key role. In this paper, we would like to discuss widely used techniques such as port based, pay-load based, behavioural based and statistical based classification models have been discussed and sample data sets are produced with graphical notations to strengthen the analysis process. So the comprehensive study on these classification models will provide the clarity on how the traffic is classified, quality of service on the various types of applications and issues of each classification model. Classification used for monitoring the security over the traffic and core element for network intrusion detection system. There are many network servicing areas where we need to identify and classify the traffic such as routing, firewall access-control, policy based routing, traffic billing need to be differentiated and their quality of service has to be assured. Inderscience Publishers - linking academia, business and industry through research

Title: A study on flow based classification models using machine learning techniques

Authors: K. Chokkanathan; S. Koteeswaran

Addresses: Department of Computer Science and Engineering, Vel Tech Dr.RR & Dr.SR Technical University, Chennai, 600062, India ' Department of Computer Science and Engineering, Vel Tech Dr.RR & Dr.SR Technical University, Chennai, 600062, India

Abstract: Network traffic management facing a lot of challenges in the recent years because of the continuous and fast development in network scale, number of consumers and type of known and unknown applications over the network. Traffic classification is a key factor for providing the quality of network services (QoS), handling the delay and congestion during the transmission. In the field of network traffic classification, Machine learning algorithms are playing key role. In this paper, we would like to discuss widely used techniques such as port based, pay-load based, behavioural based and statistical based classification models have been discussed and sample data sets are produced with graphical notations to strengthen the analysis process. So the comprehensive study on these classification models will provide the clarity on how the traffic is classified, quality of service on the various types of applications and issues of each classification model. Classification used for monitoring the security over the traffic and core element for network intrusion detection system. There are many network servicing areas where we need to identify and classify the traffic such as routing, firewall access-control, policy based routing, traffic billing need to be differentiated and their quality of service has to be assured.

Keywords: network classifications models; network traffic analysis; quality of service; intrusion detection system.

DOI: 10.1504/IJISTA.2018.095114

International Journal of Intelligent Systems Technologies and Applications, 2018 Vol.17 No.4, pp.467 - 482

Received: 18 Aug 2017
Accepted: 19 Oct 2017
Published online: 01 Oct 2018 *

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Title: A study on flow based classification models using machine learning techniques

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