An Internet traffic classification methodology based on statistical discriminators

Abstract

This work presents an Internet traffic classification methodology based on statistical discriminators and cluster analysis. An accuracy identification of Internet applications is an important research area, because it is directly related to solve many network problems such as: quality of service (QoS), traffic control, security, network management and operation. The main difference to previous approaches lies in the discriminators use; rather than using only one set of discriminators for all classes we use a set of different statistical discriminators for each traffic class. Using real traces into the training and classification phases, we validated the methodology for P2P traffic class.