• Adaptive Pursuit Learning for Energy‐efficient Target Coverage in Wireless Sensor Networks 

      Upreti, Ramesh; Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Engelstad, Paal E.; Yazidi, Anis (Concurrency and Computation: Practice and Experience; e5975, Journal article; Peer reviewed, 2020-08-25)
      With the proliferation of technologies such as wireless sensor networks (WSNs) and the Internet of things (IoT), we are moving towards the era of automation without any human intervention. Sensors are the principal components ...
    • An Adaptive User Pairing Strategy for Uplink Non-Orthogonal Multiple Access 

      Rauniyar, Ashish; Engelstad, Paal E.; Østerbø, Olav Norvald (IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops;2020 IEEE 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, Conference object, 2020-10-08)
      Non-orthogonal multiple access (NOMA) is consid-ered an important candidate for the next-generation cellular networks to address the issue of exponentially growing data traffic from technologies like the Internet of Things ...
    • Advanced passive operating system fingerprinting using machine learning and deep learning 

      Hagos, Desta Haileselassie; Løland, Martin V.; Yazidi, Anis; Kure, Øivind; Engelstad, Paal E. (International Conference on Computer Communications and Networks (ICCCN); 2020 29th International Conference on Computer Communications and Networks (ICCCN), Journal article; Peer reviewed, 2020-09-30)
      Securing and managing large, complex enterprise network infrastructure requires capturing and analyzing network traffic traces in real-time. An accurate passive Operating System (OS) fingerprinting plays a critical role ...
    • Automatic security classification by machine learning for cross-domain information exchange 

      Hammer, Hugo Lewi; Kongsgård, Kyrre Wahl; Yazidi, Anis; Bai, Aleksander; Nordbotten, Nils Agne; Engelstad, Paal E. (MILCOM IEEE Military Communications Conference;, Journal article; Peer reviewed, 2015)
      Cross-domain information exchange is necessary to obtain information superiority in the military domain, and should be based on assigning appropriate security labels to the information objects. Most of the data found ...
    • Building domain specific sentiment lexicons combining information from many sentiment lexicons and a domain specific corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Computer Science and Its Applications: 5th IFIP TC 5 International Conference, CIIA 2015, Saida, Algeria, May 20-21, 2015, Proceedings;, Peer reviewed; Chapter, 2015)
      Most approaches to sentiment analysis requires a sentiment lexicon in order to automatically predict sentiment or opinion in a text. The lexicon is generated by selecting words and assigning scores to the words, and the ...
    • Capacity Enhancement of NOMA‐SWIPT IoT Relay System with Direct Links over Rayleigh Fading Channels 

      Rauniyar, Ashish; Engelstad, Paal E.; Østerbø, Olav Norvald (Transactions on Emerging Telecommunications Technologies;Volume 31, Issue 12, Journal article; Peer reviewed, 2020-03-21)
      It is known that when the direct links between the base station (BS) and the users exist and are nonnegligible, consolidating direct links could significantly enhance the performance of the cooperative relaying systems. ...
    • Classification of Delay-based TCP Algorithms From Passive Traffic Measurements 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis (IEEE International Symposium on Network Computing and Applications;, Conference object, 2019-12-19)
      Identifying the underlying TCP variant from passive measurements is important for several reasons, e.g., exploring security ramifications, traffic engineering in the Internet, etc. In this paper, we are interested in ...
    • Crowdsourcing-based Disaster Management using Fog Computing in Internet of Things Paradigm 

      Rauniyar, Ashish; Engelstad, Paal E.; Feng, Boning; Do, van Thanh (Chapter; Peer reviewed; Chapter, 2016)
      In internet of things (IoT) paradigm, crowdsourcing is the process of obtaining and analyzing information or input to a particular task or project generated by a number of sources such as sensors, mobile devices, vehicles ...
    • A Deep Learning Approach to Dynamic Passive RTT 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Griwodz, Carsten (2019 IEEE 38th International Performance Computing and Communications Conference (IPCCC);, Conference object, 2019)
      The Round-Trip Time (RTT) is a property of the path between a sender and a receiver communicating with Transmission Control Protocol (TCP) over an IP network and over the public Internet. The end-to-end RTT value influences ...
    • A Deep Learning Approach to Dynamic Passive RTT Prediction Model for TCP 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Griwodz, Carsten (IEEE International Conference Performance, Computing and Communications (IPCCC);, Conference object, 2020-01-16)
      The Round-Trip Time (RTT) is a property of the path between a sender and a receiver communicating with Transmission Control Protocol (TCP) over an IP network and over the public Internet. The end-to-end RTT value influences ...
    • Detection of DNS tunneling in mobile networks using machine learning 

      Do, Van Thuan; Engelstad, Paal E.; Feng, Boning; Do, van Thanh (Lecture Notes in Electrical Engineering;Information Science and Applications 2017, Volume 424, Journal article; Peer reviewed, 2017)
      Lately, costly and threatening DNS tunnels on the mobile networks bypassing the mobile operator’s Policy and Charging Enforcement Function (PCEF), has shown the vulnerability of the mobile networks caused by the Domain ...
    • Energy Efficient Target Coverage in Wireless Sensor Networks Using Adaptive Learning 

      Rauniyar, Ashish; Kunwar, Jeevan; Haugerud, Hårek; Yazidi, Anis; Engelstad, Paal E. (Communications in Computer and Information Science;volume 1130, Journal article; Peer reviewed; Book chapter, 2019)
      Over the past few years, innovation in the development of Wireless Sensor Networks (WSNs) has evolved rapidly. WSNs are being used in many application fields such as target coverage, battlefield surveillance, home security, ...
    • Ergodic Capacity Performance of D2D IoT Relay NOMA-SWIPT Systems with Direct Links 

      Rauniyar, Ashish; Engelstad, Paal E.; Østerbø, Olav Norvald (International Conference on Telecommunications and Signal Processing (TSP); 2020 43rd International Conference on Telecommunications and Signal Processing (TSP), Chapter; Peer reviewed, 2020-08-11)
      We investigate the Ergodic capacity (EC) performance of device-to-device (D2D) Internet of Things (IoT) relay non-orthogonal multiple access (NOMA)- simultaneous wireless information and power transfer (SWIPT) systems where ...
    • A General Formalism for Defining and Detecting OpenFlow Rule Anomalies 

      Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E.; Kure, Øivind (Chapter; Peer reviewed, 2017)
      SDN network's policies are updated dynamically at a high pace. As a result, conflicts between policies are prone to occur. Due to the large number of switches and heterogeneous policies within a typical SDN network, detecting ...
    • General TCP state inference model from passive measurements using machine learning techniques 

      Hagos, Desta Haileselassie; Engelstad, Paal E.; Yazidi, Anis; Kure, Øivind (IEEE Access;VOLUME 6, 2018, Journal article; Peer reviewed, 2018-05-04)
      Many applications in the Internet use the reliable end-to-end Transmission Control Protocol (TCP) as a transport protocol due to practical considerations. There are many different TCP variants widely in use, and each ...
    • A graph neural approach for group recommendation system based on pairwise preferences 

      Abolghasemi, Roza; Viedma, Enrique Herrera; Engelstad, Paal E.; Djenouri, Youcef; Yazidi, Anis (Peer reviewed; Journal article, 2024)
      Pairwise preference information, which involves users expressing their preferences by comparing items, plays a crucial role in decision-making and has recently found application in recommendation systems. In this study, ...
    • Improving Classification of Tweets Using Linguistic Information from a Large External Corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Journal article; Peer reviewed, 2016)
      The bag of words representation of documents is often unsat- isfactory as it ignores relationships between important terms that do not co-occur literally. Improvements might be achieved by expanding the vocabulary with ...
    • Improving classification of tweets using word-word co-occurrence information from a large external corpus 

      Hammer, Hugo Lewi; Yazidi, Anis; Bai, Aleksander; Engelstad, Paal E. (Chapter; Peer reviewed; Chapter, 2016)
      Classifying tweets is an intrinsically hard task as tweets are short messages which makes traditional bags of words based approach ine cient. In fact, bags of words approaches ig- nores relationships between important ...
    • IncludeOS: A minimal, resource efficient unikernel for cloud services 

      Bratterud, Alfred; Walla, Alf-Andre; Haugerud, Hårek; Engelstad, Paal E.; Begnum, Kyrre (IEEE International Conference on Cloud Computing Technology and Science;2015, Journal article; Peer reviewed, 2015)
      The emergence of cloud computing as a ubiquitous platform for elastically scaling services has generated need and opportunity for new types of operating systems. A service that needs to be both elastic and resource efficient ...
    • An Incremental Approach for Swift OpenFlow Anomaly Detection 

      Aryan, Ramtin; Yazidi, Anis; Engelstad, Paal E. (2018 IEEE 43rd Conference on Local Computer Networks (LCN);, Conference object, 2018)
      Software Defined Networking (SDN) is designed for dynamic policy update where frequent changes are pushed to the forwarding devices. Different offline approaches for detecting misconfiguration anomalies in SDN by taking a ...