Browsing by Author "Grov, Gudmund"

Now showing items 1-8 of 8

    • Automating Event-B invariant proofs by rippling and proof patching 

      Lin, Yuhui; Bundy, Alan; Grov, Gudmund; Maclean, Ewen (2019-01-02)
      The use of formal method techniques can contribute to the production of more reliable and dependable systems. However, a common bottleneck for industrial adoption of such techniques is the needs for interactive proofs. We ...

    • 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. ...

    • Challenges for Risk and Security Modelling in Enterprise Architecture 

      Grov, Gudmund; Mancini, Federico; Mestl, Elsie Margrethe (2019-11-19)
      From our experience cooperating with the Norwegian Armed Forces, we outline two interconnected challenges for modelling risk and security in an enterprise architecture: (1) modelling what is protected and why it is protected ...

    • 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 ...

    • LADEMU: a modular & continuous approach for generating labelled APT datasets from emulations 

      Gjerstad, Julie; Kadiric, Fikret; Grov, Gudmund; Kjellstadli, Espen Hammer; Asprusten, Markus Leira (2023-01-26)
      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 data-driven autonomous cyber defence for military unmanned vehicles - threats & attacks 

      Kaasen, Andreas Dybvik; Grov, Gudmund; Mancini, Federico; Baksaas, Magnus (2022-11-28)
      Unmanned vehicles with varying degrees of autonomy will likely change the way military operations can be conducted, but they also introduce risks that require new ways of thinking security. In particular, the safety ...

    • Towards Privacy-First Security Enablers for 6G Networks: The PRIVATEER Approach 

      Masouros, Dimosthenis; Soudris, Dimitrios; Gardikis, Georgios; Katsarou, Victoria; Christopoulou, Maria; Xilouris, George; Ramón, Hugo; Pastor, Antonio; Scaglione, Fabrizio; Petrollini, Cristian; Pinto, Antonió; Vilela, João; Karamatskou, Antonia; Papadakis, Nikolaos; Angelogianni, Anna; Giannetsos, Thanassis; Villalba, Luis Javier García; Alonso-López, Jesús A.; Strand, Martin; Grov, Gudmund; Bikos, Anastasios N.; Ramantas, Kostas; Santos, Ricardo; Silva, Fábio; Tsampieris, Nikolaos (2023-11-07)
      The advent of 6G networks is anticipated to introduce a myriad of new technology enablers, including heterogeneous radio, RAN softwarization, multi-vendor deployments, and AI-driven network management, which is expected ...

    • Towards XAI in the SOC – a user centric study of explainable alerts with SHAP and LIME 

      Eriksson, Håkon Svee; Grov, Gudmund (2023-01-26)
      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 ...