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    DoSTDM: A denial of service detection model using firewall data traffic pattern matching

    194383_Ahmad Salem 2013.pdf (7.957Mb)
    Access Status
    Open access
    Authors
    Ahmad Salem, Mohammed Ali Mohammed
    Date
    2013
    Supervisor
    Dr Peter Dell
    Dr Helen Armstrong
    Type
    Thesis
    Award
    PhD
    
    Metadata
    Show full item record
    School
    School of Information Systems
    URI
    http://hdl.handle.net/20.500.11937/1683
    Collection
    • Curtin Theses
    Abstract

    This research deals with Denial of Service (DoS) flooding attacks. These types of attacks toward internet connected networks are on the rise. The research proposes a model that triangulate between statistical and neural network forecasting approaches. The proposed model can identify DoS attacks using the firewall rejected traffic falling outside the normal levels that could indicate a DoS attack. The triangulation approach provided the research model with multi prediction techniques with high accuracy.

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