![Fig. 3 Radial Basis Function In 2013 Mussab M. Hassan et al. [5] uses hybrid statistical traffic classifier to classify the P2P (peer to peer) traffic. Here also the works in two steps, firstly offline heuristics learning corpus generation and second is online statistical classification, In this first part, Heuristic classify the traffic flow and second part machine learning algorithm are used to classify network traffic. They apply 64 ML algorithms to classify traffic and find that RBF ML algorithms give good result. In 2010 Murat Soysal et al. [16] compare and evaluate of machine learning algorithms to classify the flow based network and they find that supervised machine learning algorithm gives the best result in traffic classification as compare to unsupervised machine learning algorithms.](https://www.researchgate.net/publication/282476570/figure/fig1/AS:643525674795031@1530439885664/Radial-Basis-Function-In-2013-Mussab-M-Hassan-et-al-5-uses-hybrid-statistical-traffic_Q320.jpg)
December 2015
·
501 Reads
·
85 Citations
Procedia Computer Science
With the advancement of technology and communication system, use of internet is giving at a tremendous role. This causes an exponential growth of data and traffic over the internet. So to correctly classify this traffic is a hot research area. Internet traffic classification is a very popular tool against the information detection system. Although so many methods had been develop to efficiently classify internet traffic but among them machine learning techniques are most popular. A brief survey on various supervised and unsupervised machine learning techniques applied by various researchers to solve internet traffic classification has been discussed. This paper also present various issues related to machine learning techniques that may help interested researchers to work future in this direction.