Ihab Sbeity^1,, Bassem Haidar¹, Mohamed Dbouk¹

Traffic classification is a process which categorizes computer network traffic according to various parameters into a number of classes or applications. The interest of internet traffic classification methods has greatly increased over the last decade. The classification methods based on the port number, or based on the payload, suffer from a number of problems, such as the dynamic port allocation and the encrypted applications. For these reasons, new approaches have been proposed without the need to know the port number, typically centered on the statistical behavior of the traffic. In this paper, we develop a novel approach based on multi-criteria decision making methods that achieves a higher significant filtering on the traffic parameters in order to obtain more accurate classification results.

Traffic Classification, Multi-criteria decision making (MCDM) methods, Analytical Hierarchy Process (AHP), Technique of Order Preference by Similarity to Ideal Solution (TOPSIS), Gaussian distribution, Gaussian mixture model (GMM)