URL: http://www.cl.cam.ac.uk/~awm22/publications/moore2005internet.pdf Entry Date: 2009-02-06 Abstract: Accurate traffic classification is of fundamental importance to numerous other network activities, from security monitoring to accounting, and from Quality #of Service to providing operators with useful forecasts for long-term provisioning. We apply a Naive Bayes estimator to categorize traffic by application. Uniquely, our work capitalizes on hand-classified network data, using it as input to a supervised Naive Bayes estimator. In this paper we illustrate the high level of accuracy achievable with the Naive Bayes estimator. We further illustrate the improved accuracy of refined variants of this estimatortions annotations Results: