Browsing Institutt for informatikk by Author "Grov, Gudmund"

Now showing items 1-4 of 4

  • 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 (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 2021)
    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 ...
  • CBAM: A Contextual Model for Network Anomaly Detection 
    Clausen, Henry; Grov, Gudmund; Aspinall, David (Journal article / Tidsskriftartikkel / PublishedVersion; Peer reviewed, 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. ...
  • LADEMU: a modular & continuous approach for generating labelled APT datasets from emulations 
    Gjerstad, Julie; Kadiric, Fikret; Grov, Gudmund; Kjellstadli, Espen Hammer; Asprusten, Markus Leira (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2023)
    Development and evaluation of data-driven capabilities for both threat hunting and intrusion detection require high-quality and up-to-date datasets. The generation of such datasets poses multiple challenges, which has led ...
  • Towards XAI in the SOC – a user centric study of explainable alerts with SHAP and LIME 
    Eriksson, Håkon Svee; Grov, Gudmund (Chapter / Bokkapittel / AcceptedVersion; Peer reviewed, 2023)
    Many studies of the adoption of machine learning (ML) in Security Operation Centres (SOCs) have pointed to a lack of transparency and explanation – and thus trust – as a barrier to ML adoption, and have suggested eXplainable ...