The Impact of Evasion on the Generalization of Machine Learning Algorithms to Classify VoIP Traffic

Abstract

We propose a novel approach to generate well generalized signatures to classify Skype VoIP traffic using a machine learning based approach. Results show that the performance of the signatures did not degrade significantly when they were evaluated on traffic that was captured from different locations and at different times as well as employed against evasion… (More)
DOI: 10.1109/ICCCN.2012.6289243

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