Now showing items 1-2 of 2

    • CBAM: A Contextual Model for Network Anomaly Detection 

      Clausen, Henry; Grov, Gudmund; Aspinall, David (2021)
      Anomaly-based intrusion detection methods aim to combat the increasing rate of zero-day attacks, however, their success is currently restricted to the detection of high-volume attacks using aggregated traffic features. ...
    • A containerised approach to labelled C&C traffic 

      Asprusten, Markus Leira; Gjerstad, Julie Lidahl; Grov, Gudmund; Kjellstadli, Espen Hammer; Flood, Robert; Clausen, Henry; Aspinall, David (2022-01-24)
      A challenge for data-driven methods for intrusion detection is the availability of high quality and realistic data, with ground truth at suitable level of granularity to train machine learning models. Here, we explore a ...