• Datalagringsdirektivet 

      Leren, Eystein Huse (Master thesis, 2009)
      Datalagringsdirektivet EU 2006/24/EF har til hensikt å harmonisere lovgivningen som gjelder lagring av trafikkdata gjennom hele EU området, og gjennom dette gjøre medlemslandene bedre rustet til å bekjempe alvorlig ...
    • The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies 

      Sayers, Dave; Sousa-Silva, Rui; Höhn, Sviatlana; Ahmedi, Lule; Allkivi-Metsoja, Kais; Anastasiou, Dimitra; Beňuš, Štefan; Bowker, Lynne; Bytyçi, Eliot; Catala, Alejandro; Çepani, Anila; Chacón-Beltrán, Rubén; Dadi, Sami; Dalipi, Fisnik; Despotovic, Vladimir; Doczekalska, Agnieszka; Drude, Sebastian; Fort, Karën; Fuchs, Robert; Galinski, Christian; Gobbo, Federico; Gungor, Tunga; Guo, Siwen; Höckner, Klaus; Láncos, PetraLea; Libal, Tomer; Jantunen, Tommi; Jones, Dewi; Klimova, Blanka; Korkmaz, EminErkan; Maučec, Mirjam Sepesy; Melo, Miguel; Meunier, Fanny; Migge, Bettina; Mititelu, Verginica Barbu; Névéol, Aurélie; Rossi, Arianna; Pareja-Lora, Antonio; Sanchez-Stockhammer, C.; Şahin, Aysel; Soltan, Angela; Soria, Claudia; Shaikh, Sarang; Turchi, Marco; Yildirim Yayilgan, Sule; Bessa, Maximino; Cabral, Luciana; Coler, Matt; Liebeskind, Chaya; Kernerman, Ilan; Rousi, Rebekah; Prys, Cynog (Research report, 2021)
      New language technologies are coming, thanks to the huge and competing private investment fuelling rapid progress; we can either understand and foresee their effects, or be taken by surprise and spend our time trying to ...
    • DDoS attacks and Countermeasures 

      Rajanna, Puneeth Prasad (Master thesis, 2010)
      Internet has grown leaps and bounds over the last few decades. Internet's phenomenal growth it has attracted users with malicious intent. Distributed Denial of Service (DDoS) attacks have become very common these days. The ...
    • Death anxiety and visual oculomotor processing of arousing stimuli in a free view setting 

      Wendelberg, Linda; Volden, Frode; Yildirim, Sule (Journal article; Peer reviewed, 2017)
      The main goal of this study was to determine how death anxiety (DA) affects visual processing when confronted with arousing stimuli. A total of 26 males and females were primed with either DA or a neutral primer and were ...
    • Decentralized Identity Management Systems and Self-Sovereign Identity 

      Strindberg, Jan Magnus (Master thesis, 2019)
      Med den økende interessen for blockchain-teknologi, foreslås en rekke applikasjoner og bruksområder. Bruk av blockchain til å skape desen- traliserte identitetsstyringssystemer er et lovende bruksområde. Dette skyldes ...
    • Decentralized Self-Enforcing Trust Management System for Social Internet of Things 

      Azad, Muhammad Ajmal; Bag, Samiran; Feng, Hao; Shalaginov, Andrii (Peer reviewed; Journal article, 2020)
      The Internet of Things (IoT) is the network of connected computing devices that have the ability to transfer valued data between each other via the Internet without requiring human intervention. In such a connected ...
    • Decoding GSM 

      Glendrange, Magnus; Hove, Kristian; Hvideberg, Espen (Master thesis, 2010)
      We have participated in the creation of almost two terabytes of tables aimed at cracking A5/1, the most common ciphering algorithm used in GSM. Given 114-bit of known plaintext, we are able to recover the session key with ...
    • Deep Composite Face Image Attacks: Generation, Vulnerability and Detection 

      Singh, Jag Mohan; Ramachandra, Raghavendra (Peer reviewed; Journal article, 2023)
      Face manipulation attacks have drawn the attention of biometric researchers because of their vulnerability to Face Recognition Systems (FRS). This paper proposes a novel scheme to generate Composite Face Image Attacks ...
    • Deep Face Age Progression: A Survey 

      Grimmer, Marcel; Ramachandra, Raghavendra; Busch, Christoph (Peer reviewed; Journal article, 2021)
    • Deep Graph neural network-based spammer detection under the perspective of heterogeneous cyberspace 

      Guo, Zhiwei; Tang, Lianggui; Guo, Tan; Yu, Keping; Alazab, Mamoun; Shalaginov, Andrii (Peer reviewed; Journal article, 2021)
      Due to the severe threat to cyberspace security, detection of online spammers has been a universal concern of academia. Nowadays, prevailing literature of this field almost leveraged various relations to enhance feature ...
    • Deep Learning Algorithms in Health Area: Adversarial Attacks and Countermeasures 

      Nedellec, Maël; Mouret, Quentin (Master thesis, 2021)
      Nowadays, in the health area, Artificial Intelligence (AI) becomes a must-have to improve diagnosis and prognosis quality. Thus, the medical corps can use Deep Learning (DL) algorithms to predict the evolution of diseases, ...
    • Deep Learning Algorithms in Health Area: Adversarial Attacks and Countermeasures 

      Nedellec, Maël; Mouret, Quentin (Master thesis, 2021)
      Nowadays, in the health area, Artificial Intelligence (AI) becomes a must-have to improve diagnosis and prognosis quality. Thus, the medical corps can use Deep Learning (DL) algorithms to predict the evolution of diseases, ...
    • Deep Learning Based Approaches for Financial Fraud Detection 

      Nan, Zhang (Master thesis, 2020)
      Oppdagelse av økonomisk svindel er et irriterende problem som tar finansinstitusjoner mye penger og energi for å redusere tapet forårsaket av det. Tradisjonelle metoder for oppdagelse av svindel trenger mye trent revisjoner ...
    • Deep learning based Sequential model for malware analysis using Windows exe API Calls 

      Catak, Ferhat Özgur; Yazi, Ahmet Faruk; Elezaj, Ogerta; Ahmed, Javed (Peer reviewed; Journal article, 2020)
      Malware development has seen diversity in terms of architecture and features. This advancement in the competencies of malware poses a severe threat and opens new research dimensions in malware detection. This study is ...
    • Deep Learning for Fingerprint Recognition Systems 

      Schuch, Patrick (Doctoral theses at NTNU;2019:242, Doctoral thesis, 2019)
      Summary Biometric recognition is a typical means to identify individuals or to verify claimed identities. Use cases are manifold. For example, users can unlock their smartphones for convenience by presenting their faces ...
    • Deep learning in health systems: An analysis of adversarial attacks on convolutional neural networks 

      Orvedal, Vegard Andreas (Master thesis, 2022)
      Det siste tiårets utvikling av kovolusjonelle nevrale nettverk has revolusjonert bildegjenkjenningsfagfeltet innen kunstig intelligens. Innen helse har nye dype nevrale nettverk blitt vist å gjenkjenne diagnoser bedre enn ...
    • Deep Learning Techniques for Face Image Quality Estimation 

      Thorsen, Tommy (Master thesis, 2018)
      Biometric authentication using fingerprints or face recognition is becoming mainstream, and there is a need to make these methods as secure and reliable as possible. One way to achieve better performance with a biometric ...
    • Deep Neural Network based Malicious Network Activity Detection Under Adversarial Machine Learning Attacks 

      Catak, Ferhat Özgur; Yildirim Yayilgan, Sule (Journal article, 2021)
    • Deep Packet Inspection Bypass 

      Kjøglum, Thomas (Master thesis, 2015)
      Internet censorship is a problem, where governments and authorities restricts access to what the public can read on the Internet. They use deep packet inspection tools to conduct the censorship. An example of such a tool ...
    • Deep-STRESS Capsule Video Endoscopy Image Enhancement 

      Mohammed, Ahmed Kedir; Pedersen, Marius; Hovde, Øistein; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2018)
      This paper proposes a unified framework for capsule video endoscopy image enhancement with an objective to enhance the diagnostic values of these images. The proposed method is based on a hybrid approach of deep learning ...