摘要: To manage and monitor their networks in a proper way, network operators are often interested identifying the applications generating traffic traveling through networks, doing it as fast (i.e., from few packets) possible. State-of-the-art packet-based classification methods either based on costly inspection of payload several packets each flow or basic statistics that do not take into account packet content. In this paper we consider intermediate approach analyzing only first bytes (or few) flow. We propose automatic, machine-learning-based achieving remarkably good early performance real traces generated diverse set (including versions P2P TV file sharing), while requiring limited computational memory resources.
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