Novel context-aware network traffic classification based on a machine learning approach

Ahmed Saeed & Mario Kolberg
The dataset was constructed by capturing real-time background traffic of 9 applications. The 9 applications represent different types of network behaviour in the background, for high level of networkinteraction; we have considered video and voice calls of Skype and Google Hangouts. For the varied level of interactions Facebook and Gmail been chosen, for Gmail, emails were received at random instances. And tagged posts were received at random instances for Facebook as updates. NSS and NSC...
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