Flow traffic classification with support vector machine by using payload length

Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. In this paper, we propose flow traffic classification methods using support vector machine. Classifying traffic is an important task for effective network planning and design, and monitoring the trends of the applications in operational networks. The proposals satisfy the following three requirements. Using to only flow information, not using port numbers, automatic making of traffic models. In this paper, we provide an empirical evaluation of our proposals using datasets of MIT Lincoln Laboratory, which illustrates that our proposals can classify network traffic flow over 90 % precision.