Learning for accurate classification of real-time traffic

Accurate network traffic classification is an important task. We intend to develop an intelligent classification system by learning the types of service inside a network flow using machine learning techniques. Previous work used Bayesian methods for traffic classification. In this paper we propose a further plan to identify a fine-grained traffic classification scheme through combining a series of techniques.