This paper proposes a new technique, flow-based traffic retrieval (FBTR), to find traffic flows that satisfy an information need from within large collections of network traffic. It is shown that flow-based traffic retrieval will become a powerful tool in network management and security. For example, the retrieved traffic flows can be used to help analysing new applications/protocols and detecting unknown attacks. In the context of flow-based traffic retrieval, a traffic flow is represented by a vector that consists of a set of flow statistics, such as the average of packet sizes and the average of inter-packet times. The user can submit a traffic flow, or several traffic flows, and ask for “similar” traffic flows to be retrieved from a traffic collection. Similarity search is based on comparing flow vectors in a feature space. We have done some preliminary experiments to evaluate the performance of flow-based traffic retrieval. The results show flow-based traffic retrieval has potential to quickly and accurately find user-interested network traffic, even encrypted traffic.


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    Titel :

    Flow-based traffic retrieval using statistical features


    Beteiligte:
    Zhang, Jun (Autor:in) / Goscinski, Andrzej (Autor:in)


    Erscheinungsdatum :

    01.10.2016


    Format / Umfang :

    448440 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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