• Login
    View Item 
    •   SU+ Home
    • Conferences / Workshops / Seminars +
    • Pan African Conference on Science, Computing and Telecommunications (PACT) 2017
    • View Item
    •   SU+ Home
    • Conferences / Workshops / Seminars +
    • Pan African Conference on Science, Computing and Telecommunications (PACT) 2017
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Detecting scanning computer worms using machine learning and darkspace network traffic

    Thumbnail
    View/Open
    Full text (257.5Kb)
    Date
    2017
    Author
    Ochieng, Nelson
    Ismail, Ateya
    Waweru, Mwangi
    Orero, Joseph
    Metadata
    Show full item record
    Abstract
    The subject of this paper is computer worm detection in a network. Computers worms have been defined as a process that can cause a possibly evolved copy of it to execute on a remote computer. They do not require human intervention to propagate; neither do they need to attach themselves to existing files. Computer worms spread very rapidly and modern worm authors obfuscate their code to make it difficult to detect them. This paper proposes to use machine learning to detect them. The paper deviates from existing approaches in that it uses the darkspace network traffic attributed to an actual worm attack to validate the algorithms. In addition, it attempts to understand the threat model, the feature set and the detection algorithms to explain the best combination of features and why the best algorithms succeeds where others have failed.
    URI
    http://hdl.handle.net/11071/5182
    Collections
    • Pan African Conference on Science, Computing and Telecommunications (PACT) 2017 [20]

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV
     

     

    Browse

    All of SU+Communities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    Login

    DSpace software copyright © 2002-2016  DuraSpace
    Contact Us | Send Feedback
    Theme by 
    Atmire NV