• A novel feature selection technique in Android malware detection systems 

      Golrang, Anahita (Master thesis, 2020)
      The sale statistics of mobile devices demonstrate that Android has achieved the highest market share among the present operating systems in the mobile industry which provides more incentives for the attackers to generate ...
    • Border Control and Use of Biometrics: Reasons Why the Right to Privacy Can Not Be Absolute 

      Abomhara, Mohamed; Yildirim Yayilgan, Sule; Shalaginova, Marina; Székely, Zoltán (Chapter, 2020)
      This paper discusses concerns pertaining to the absoluteness of the right to privacy regarding the use of biometric data for border control. The discussion explains why privacy cannot be absolute from different points of ...
    • A comparison of primary stakeholders views on the deployment of biometrics technology in border management: Case study of smart mobility at the European land borders 

      Abomhara, Mohamed; Yildirim Yayilgan, Sule; Nweke, Livinus Obiora; Székely, Zoltán (Peer reviewed; Journal article, 2021)
      Advances in technology have a substantial impact on every aspect of our lives, ranging from the way we communicate to the way we travel. The Smart mobility at the European land borders (SMILE) project is geared towards the ...
    • Crime Intelligence from Social Media Using CISMO 

      Elezaj, Ogerta; Yildirim Yayilgan, Sule; Ahmed, Javed; Kalemi, Edlira; Brichfeld, Brumle; Haubold, Claudia (Peer reviewed; Journal article, 2020)
      Nowadays, online social networks (OSNs) are being used as a hosting ground for criminal activities, and the legal enforcement agencies (LEAs) are struggling to process and analyse the huge amount of data coming from these ...
    • Criminal Network Community Detection in Social Media Forensics 

      Elezaj, Ogerta; Yildirim Yayilgan, Sule (Peer reviewed; Journal article, 2021)
      Nowadays, Online Social Networks (OSNs) has created a breeding ground for criminals to engage in cyber–crime activities, and the legal enforcement agencies (LEAs) are facing significant challenges since there is no consistent ...
    • Cyber-Security Gaps in a Digital Substation: From Sensors to SCADA 

      Khodabakhsh, Athar; Yildirim Yayilgan, Sule; Houmb, Siv Hilde; Hurzuk, Nargis; Foros, Jørn; Istad, Maren Kristine (Chapter, 2020)
      Development of digital substations provides power industrial operation, real-time functionalities and information access. A main challenge in DS is to ensure security, availability, and reliability of power systems as in ...
    • Data-driven Intrusion Detection System for Small and Medium Enterprises 

      Elezaj, Ogerta; Yildirim Yayilgan, Sule; Abomhara, Mohamed Ali Saleh; Yeng, Prosper; Ahmed, Javed (Journal article; Peer reviewed, 2019)
      Small and Medium Enterprises (SMEs) have become targets of attack by cyber criminals in resent times. This paper therefore aim to address awareness and challenges of SMEs related to IDSs as the most important defense tool ...
    • Data-Driven Machine Learning Approach for Human Action Recognition Using Skeleton and Optical Flow 

      Lee, Yen-Ting; Pengying, Thitinun; Yildirim Yayilgan, Sule; Elezaj, Ogerta (Chapter, 2021)
      Human action recognition is a very challenging problem due to numerous variations in each body part. In this paper, we propose a method for extracting optical flow information from skeleton data to address the problem of ...
    • 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 ...
    • 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 Neural Network based Malicious Network Activity Detection Under Adversarial Machine Learning Attacks 

      Catak, Ferhat Özgur; Yildirim Yayilgan, Sule (Journal article, 2021)
    • Deep Smoke Removal from Minimally Invasive Surgery Videos 

      Bolkar, Sabri; Wang, Congcong; Alaya Cheikh, Faouzi; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2018)
      During video-guided minimally invasive surgery, quality of frames may be degraded severely by cauterization-induced smoke and condensation of vapor. This degradation of quality creates discomfort for the operating surgeon, ...
    • 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 ...
    • Distribution of fiscal coupons via Genetic Algorithms and Greedy Randomized Adaptive Search Procedure 

      Sylejmani, Kadri; Hyseni, Qëndresë; Yildirim Yayilgan, Sule; Qurdina, Agon; Mula, Leke; Krasniqi, Bujar (Journal article; Peer reviewed, 2018)
      When customers buy goods or services from business entities they are usually given a receipt that is known with the name fiscal or tax coupon, which, among the others, contains details about the value of the transaction. ...
    • How to do it right: A framework for biometrics supported border control 

      Abomhara, Mohamed Ali Saleh; Yildirim Yayilgan, Sule; Nymoen, Anne Hilde Ruen; Shalaginova, Marina; Székely, Zoltán; Elezaj, Ogerta (Journal article; Peer reviewed, 2019)
      Complying with the European Union (EU) perspective on human rights goes or should go together with handling ethical, social and legal challenges arising due to the use of biometrics technology as border control technology. ...
    • The Importance Of Skip Connections In Encoder-Decoder Architectures For Colorectal Polyp Detection 

      Mulliqi, Nita; Yildirim Yayilgan, Sule; Mohammed, Ahmed Kedir; Ahmedi, Lule; Wang, Hao; Elezaj, Ogerta; Hovde, Øistein (Chapter, 2020)
      Accurate polyp detection during the colonoscopy procedure impacts colorectal cancer prevention and early detection. In this paper, we investigate the influence of skip connections as the main component of encoder-decoder ...
    • Mobile-Based Painting Photo Retrieval using Combined Features 

      Companioni-Brito, Claudia; Mariano, Zygred; Elawady, Mohamed; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2018)
      In paintings or artworks, sharing a photo of a painting using mobile phone is simple and fast. However, searching for information about specific captured photo of an unknown painting takes time and is not easy. No previous ...
    • The multi-objective feature selection in Android malware detection system 

      Mohammadi Golrang, Anahita; Yildirim Yayilgan, Sule; Elezaj, Ogerta (Peer reviewed; Journal article, 2021)
      The Android operating system boosts a global market share over the previous years, which has made it the most popular operating system in the world. Recently, Android has become the target of attacks by cybercriminals ...
    • A Novel hybrid IDS based on modified NSGAII-ANN and Random Forest 

      Golrang, Anahita; Golrang, Alale; Yildirim Yayilgan, Sule; Elezaj, Ogerta (Peer reviewed; Journal article, 2020)
      Machine-learning techniques have received popularity in the intrusion-detection systems in recent years. Moreover, the quality of datasets plays a crucial role in the development of a proper machine-learning approach. ...
    • Optimised Deep Learning Features for Improved Melanoma Detection 

      Majtner, Tomas; Yildirim Yayilgan, Sule; Hardeberg, Jon Yngve (Journal article; Peer reviewed, 2018)
      In this article, we are addressing the question of effective usage of the feature set extracted from deep learning models pre-trained on ImageNet. Exploring this option will offer very fast and attractive alternative to ...