Blar i NTNU Open på forfatter "Elezaj, Ogerta"

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    • 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 ...

    • Application of Machine Learning in IoT enabled Smart Grids for Attack Detection 

      Abraham, Doney (Master thesis, 2020)
      Smarte strømnettsløsninger har blitt anvendt i større grad i nyere tid for kritisk infrastruktur med tanke på testing og utprøving i både stor og liten skala. Slike strømnettsløsninger kombinert med IoT har potensiale til ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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 ...

    • 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. ...

    • Practical Implementation of Privacy Preserving Clustering Methods Using a Partially Homomorphic Encryption Algorithm 

      Catak, Ferhat Özgur; Aydin, Ismail; Elezaj, Ogerta; Yildirim Yayilgan, Sule (Journal article; Peer reviewed, 2020)
      The protection and processing of sensitive data in big data systems are common problems as the increase in data size increases the need for high processing power. Protection of the sensitive data on a system that contains ...

    • Towards Designing a Knowledge Graph-Based Framework for Investigating and Preventing Crime on Online Social Networks 

      Elezaj, Ogerta; Yildirim Yayilgan, Sule; Kalemi, Edlira; Wendelberg, Linda; Abomhara, Mohamed Ali Saleh; Ahmed, Javed (Journal article; Peer reviewed, 2019)
      Online Social Networks (OSNs) have fundamentally and permanently altered the arena of digital and classical crime. Recently, law enforcement agencies (LEAs) have been using OSNs as a data source to collect Open Source ...