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  3. Håvard Dagenborg
Bilde av Dagenborg, Håvard
Bilde av Dagenborg, Håvard
Professor Department of Computer Science havard.dagenborg@uit.no +4777646738 +47 91110987

Håvard Dagenborg

Job description

Prof. Håvard J. Dagenborg teaches and researches computer security and privacy topics. His work in overlay networks received great acclaim in the research community, providing a completely different way of approaching the problem of Byzantine fault tolerance. Dagenborg is currently focused on secure remote execution of code using Intel SGX, reactive information-flow policies, and energy-efficient blockchains based on Byzantine consensus. Dagenborg is a hands-on, full-stack software developer. He has up-to-date expertise with modern software technologies like GO, TypeScript, iOS/Android platforms, and Docker. Prof. Dagenborg also has competence in machine learning and interdisciplinary experiences in the medical, sports, and psychology domains.

Work areas

Research infrastructure / Research data management / Mobile / Software architecture / Applications / Servers and operating services / Security / Systems design / Interfaculty research areas
  • Stefan Kutschera, Wolfgang Slany, Patrick Ratschiller, Sarina Gursch, Patrick Deininger, Håvard Johansen Dagenborg :
    Incidental Data: A Survey towards Awareness on Privacy-Compromising Data Incidentally Shared on Social Media
    Journal of Cybersecurity and Privacy (JCP) 2024 ARKIV / DOI
  • Areeg Samir Ahmed Elgazazz, Håvard Johansen Dagenborg :
    Misconfiguration of Cluster and IoT Systems Recovery: Extended Experiments
    Springer 2024 DOI
  • Enrico Tedeschi, Håvard Johansen Dagenborg, Dag Johansen, Øyvind Arne-Moen Nohr :
    Mining Profitability in Bitcoin: Calculations of User-Miner Equilibria and Cost of Mining
    Lecture Notes in Computer Science (LNCS) 2024 DOI
  • Cise Midoglu, Andreas Kjæreng Winther, Matthias Boeker, Susann Dahl Pettersen, Sigurd Pedersen, Nourhan Ragab et al.:
    A large-scale multivariate soccer athlete health, performance, and position monitoring dataset
    Scientific Data 2024 ARKIV / DOI
  • Mohsin Khan, Håvard Johansen Dagenborg, Dag Johansen :
    Performance Evaluation of Lightweight Stream Ciphers for Real-Time Video Feed Encryption on ARM Processor
    Future Internet 2024 ARKIV / DOI
  • Areeg Samir Ahmed Elgazazz, Håvard Dagenborg :
    A Self-Configuration Controller To Detect, Identify, and Recover Misconfiguration At IoT Edge Devices and Containerized Cluster System
    ICISSP 2023 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Håvard Dagenborg, Pål Halvorsen, Michael Alexander Riegler, Dag Johansen :
    Fishing Trawler Event Detection: An Important Step Towards Digitization of Sustainable Fishing
    IEEE conference proceedings 2023 ARKIV / DOI
  • Stefan Kutschera, Wolfgang Slany, Patrick Ratschiller, Sarina Gursch, Håvard Dagenborg :
    MRNG: Accessing Cosmic Radiation as an Entropy Source for a Non-Deterministic Random Number Generator
    Entropy 2023 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Michael Riegler, Håvard Johansen Dagenborg, Dag Johansen :
    Arctic HARE: A Machine Learning-Based System for Performance Analysis of Cross-Country Skiers
    Springer 2023 ARKIV / DOI
  • Aakash Sharma, Katja Pauline Czerwinska, Dag Johansen, Håvard Johansen Dagenborg :
    Capturing Nutrition Data for Sports: Challenges and Ethical Issues
    Springer 2023 ARKIV / DOI
  • Areeg Samir Ahmed Elgazazz, Håvard Johansen Dagenborg :
    Self-Healing Misconfiguration of Cloud-Based IoT Systems Using Markov Decision Processes
    International Conference on Cloud Computing and Services Science (CLOSER) 2023 DOI
  • Lars Brenna, Isak Sunde Singh, Håvard D. Johansen, Dag Johansen :
    TFHE-rs: A library for safe and secure remote computing using fully homomorphic encryption and trusted execution environments
    Array 2022 ARKIV / DOI
  • Nikhil Kumar Tomar, Debesh Jha, Michael Riegler, Håvard D. Johansen, Dag Johansen, Jens Rittscher et al.:
    FANet: A Feedback Attention Network for Improved Biomedical Image Segmentation
    IEEE Transactions on Neural Networks and Learning Systems 2022 ARKIV / DOI
  • Enrico Tedeschi, Tor-Arne Schmidt Nordmo, Dag Johansen, Håvard D. Johansen :
    On Optimizing Transaction Fees in Bitcoin using AI: Investigation on Miners Inclusion Pattern
    ACM Transactions on Internet Technology 2022 ARKIV / DOI
  • Pietro Randine, Aakash Sharma, Gunnar Hartvigsen, Håvard D. Johansen, Eirik Årsand :
    Information and communication technology-based interventions for chronic diseases consultation: Scoping review
    International Journal of Medical Informatics 2022 ARKIV / DOI
  • Aakash Sharma, Thomas Bye Nilsen, Sivert Johansen, Dag Johansen, Håvard D. Johansen :
    Designing a Service for Compliant Sharing of Sensitive Research Data
    Lecture Notes in Computer Science (LNCS) 2022 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Ove Kvalsvik, Svein Ove Kvalsund, Birte Hansen, Pål Halvorsen, Steven Hicks et al.:
    FishAI: Sustainable Commercial Fishing Challenge
    Nordic Machine Intelligence (NMI) 2022 ARKIV / DOI
  • Areeg Samir Ahmed Elgazazz, Håvard D. Johansen :
    Technical Viewpoint of Challenges, Opportunities, and Future Directions of Policy Change and Information-Flow in Digital Healthcare Systems
    International Academy, Research and Industry Association (IARIA) 2022 ARKIV
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven Hicks, Vajira L B Thambawita, Håvard D. Johansen et al.:
    Njord: a fishing trawler dataset
    ACM Publications 2022 ARKIV / DOI
  • Debesh Jha, Ashish Rauniyar, Håvard D. Johansen, Dag Johansen, Michael Alexander Riegler, Pål Halvorsen et al.:
    Video Analytics in Elite Soccer: A Distributed Computing Perspective
    Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop 2022 ARKIV / DOI
  • Joakim Aalstad Alslie, Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Håvard D. Johansen, Pål Halvorsen, Michael Riegler et al.:
    Áika: A Distributed Edge System for AI Inference
    Big Data and Cognitive Computing 2022 ARKIV / DOI
  • Aakash Sharma, Thomas Bye Nilsen, Katja Pauline Czerwinska, Daria Onitiu, Lars Brenna, Dag Johansen et al.:
    Up-to-the-Minute Privacy Policies via Gossips in Participatory Epidemiological Studies
    Frontiers in Big Data 13. May 2021 ARKIV / DOI
  • Vajira L B Thambawita, Steven Hicks, Jonas L Isaksen, Mette H. Stensen, Trine B. Haugen, Jørgen K Kanters et al.:
    DeepSynthBody: the beginning of the end for data deficiency in medicine
    IEEE conference proceedings 2021 DOI
  • Debesh Jha, Sharib Ali, Krister Emanuelsen, Steven Hicks, Vajira L B Thambawita, Enrique Garcia-Ceja et al.:
    Kvasir-Instrument: Diagnostic and Therapeutic Tool Segmentation Dataset in Gastrointestinal Endoscopy
    Springer 2021 DOI
  • Nikhil Kumar Tomar, Debesh Jha, Sharib Ali, Håvard D. Johansen, Dag Johansen, Michael Riegler et al.:
    DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation
    Springer Nature 2021 DOI
  • Debesh Jha, Sharib Ali, Nikhil Kumar Tomar, Michael Alexander Riegler, Dag Johansen, Håvard D. Johansen et al.:
    Exploring Deep Learning Methods for Real-Time Surgical Instrument Segmentation in Laparoscopy
    IEEE (Institute of Electrical and Electronics Engineers) 2021 DOI
  • Debesh Jha, Anis Yazidi, Michael Alexander Riegler, Dag Johansen, Håvard D. Johansen, Pål Halvorsen :
    LightLayers: Parameter Efficient Dense and Convolutional Layers for Image Classification
    Springer Nature 2021 ARKIV / DOI
  • Abhishek Srivastava, Debesh Jha, Sukalpa Chanda, Umapada Pal, Håvard D. Johansen, Dag Johansen et al.:
    MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
    IEEE Journal of Biomedical and Health Informatics 2021 ARKIV / DOI
  • Aril Bernhard Ovesen, Tor-Arne Schmidt Nordmo, Håvard D. Johansen, Michael Alexander Riegler, Pål Halvorsen, Dag Johansen :
    File system support for privacy-preserving analysis and forensics in low-bandwidth edge environments
    Information 2021 ARKIV / DOI
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Håvard D. Johansen, Michael Alexander Riegler, Pål Halvorsen, Dag Johansen :
    Dutkat: A Multimedia System for Catching Illegal Catchers in a Privacy-Preserving Manner
    ACM Digital Library 2021 DOI
  • Debesh Jha, Sharib Ali, Nikhil Kumar Tomar, Håvard D. Johansen, Dag Johansen, Jens Rittscher et al.:
    Real-Time Polyp Detection, Localization and Segmentation in Colonoscopy Using Deep Learning
    IEEE Access 2021 ARKIV / DOI
  • Aakash Sharma, Katja Pauline Czerwinska, Dag Johansen, Håvard Dagenborg :
    Capturing Nutrition Data for Sports: Challenges and Ethical Issues
    2023 ARKIV
  • Areeg Samir Ahmed Elgazazz, Håvard Johansen Dagenborg :
    Adaptive Controller to Identify Misconfigurations and Optimize the Performance of Kubernetes Clusters and IoT Edge Devices
    2023 ARKIV
  • Areeg Samir Ahmed Elgazazz, Abdo Al-Wosabi, Mohsin Khan, Håvard Johansen Dagenborg :
    A Multi-pronged Self-adaptive Controller for Analyzing Misconfigurations for Kubernetes Clusters and IoT Edge Devices
    2023 ARKIV
  • Areeg Samir Ahmed Elgazazz, Håvard Johansen Dagenborg :
    A Self-Configuration and Healing Controller To Analyze Misconfigurations of Clusters and IoT Edge Devices
    2023 ARKIV
  • Håvard Johansen Dagenborg :
    Data Collection, Privacy, and Data Security 
    2023
  • Tor-Arne Schmidt Nordmo, Ove Kvalsvik, Svein Ove Kvalsund, Birte Hansen, Pål Halvorsen, Steven Hicks et al.:
    FishAI: Sustainable Commercial Fishing Challenge
    Nordic Machine Intelligence (NMI) 2022 DOI
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven A. Hicks, Vajira Thambawita, Håvard D. Johansen et al.:
    Njord: A Fishing Trawler Dataset
    2022
  • Dag Johansen, Håvard D. Johansen, Michael Riegler :
    Muligheter og skranker for bruk av teknologi og kunstig intelligens ved forebygging av fiskerikriminalitet
    2022
  • Michael Alexander Riegler, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Njord: An out-in-the-wild real world fish vessel catch analysis dataset
    2022
  • Håvard D. Johansen, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Sustainable commercial fishing: Digital inspectors to the rescue
    2022
  • Håvard D. Johansen, Dag Johansen, Areeg Samir Ahmed Elgazazz, Thomas Bye Nilsen, Aakash Sharma :
    Datainnsamling med personvern og datasikkerhet
    2022
  • Michael Alexander Riegler, Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen et al.:
    Njord: An out-in-the-wild real world fish vessel catch analysis dataset
    Arctic Frontiers : Abstracts 2022
  • Dag Johansen, Bjørn Aslak Juliussen, Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Pål Halvorsen, Håvard D. Johansen et al.:
    Sustainable commercial fishing: Digital inspectors to the rescue
    Arctic Frontiers : Abstracts 2022
  • Tor-Arne Schmidt Nordmo, Aril Bernhard Ovesen, Bjørn Aslak Juliussen, Steven A. Hicks, Vajira Thambawita, Håvard D. Johansen et al.:
    Njord: A Fishing Trawler Dataset
    2022
  • Areeg Samir Ahmed Elgazazz, Håvard Johansen Dagenborg :
    Managing Healthcare Information Flow Within Multi-Cluster System in Distributed Environment: Challenges, Opportunities and Future Directions
    International Conference on Cloud Computing and Services Science (CLOSER) 2022
  • Aakash Sharma, Thomas Bye Nilsen, Håvard D. Johansen :
    Compliant Sharing of Sensitive Data with Dataverse and Lohpi
    2021 ARKIV
  • Nikhil Kumar Tomar, Debesh Jha, Sharib Ali, Håvard D. Johansen, Dag Johansen, Michael Riegler et al.:
    DDANet: Dual Decoder Attention Network for Automatic Polyp Segmentation
    2021
  • Debesh Jha, Sharib Ali, Krister Emanuelsen, Steven Hicks, Vajira L B Thambawita, Enrique Garcia-Ceja et al.:
    Kvasir-Instrument: Diagnostic and Therapeutic Tool Segmentation Dataset in Gastrointestinal Endoscopy
    2021
  • Debesh Jha, Sharib Ali, Nikhil Kumar Tomar, Håvard D. Johansen, Dag Johansen, Michael Riegler et al.:
    Exploring Deep Learning Methods for Real-Time Surgical Instrument Segmentation in Laparoscopy
    2021 FULLTEKST

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