Recent Submissions

  • Mitigation of H.264 and H.265 Video Compression for Reliable PRNU Estimation 

    Altinisik, Enes; Tasdemir, Kasim; Sencar, Hüsrev Taha (Institute of Electrical and Electronics Engineers Inc., 2020)
    The photo-response non-uniformity (PRNU) is a distinctive image sensor characteristic, and an imaging device inadvertently introduces its sensor's PRNU into all media it captures. Therefore, the PRNU can be regarded as a ...
  • On efficient computation of equilibrium under social coalition structures 

    Çaşkurlu, Buğra; Ekici, Ozgun; Kizilkaya, Fatih Erdem (Turkiye Klinikleri, 2020)
    In game-theoretic settings the key notion of analysis is an equilibrium, which is a profile of agent strategies such that no viable coalition of agents can improve upon their coalitional welfare by jointly changing their ...
  • A study on public perception and preferences about IoT security 

    Tok, M.S.; Selçuk, Ali Aydın (Institute of Electrical and Electronics Engineers Inc., 2019-09)
    Configuring internet of things (IoT) devices with easy or default passwords leads to serious vulnerabilities. In recent years, malware (Mirai etc.) which are capable of creating IoT botnets and organizing distributed denial ...
  • HSV Color Histogram Based Image Retrieval with Background Elimination 

    Erkut, U.; Bostancioglu, F.; Erten, M.; Özbayoğlu, Ahmet Murat; Solak, E. (Institute of Electrical and Electronics Engineers Inc., 2019-11)
    In this study, a new content based image retrieval (CBIR) method, which uses HSV histogram data is proposed. The model uses the HSV histogram to find the background from the image by analyzing the peaks in the histogram data ...
  • JpgScraper : An Advanced Carver for JPEG Files 

    Uzun, Erkam; Sencar, Hüsrev Taha (Institute of Electrical and Electronics Engineers Inc., 2020)
    Orphaned file fragment carving is concerned with recovering contents of encoded data in the absence of any coding metadata. Constructing an orphaned file carver requires addressing three challenges: a specialized decoder ...
  • Evasion Techniques Efficiency over the IPS/IDS Technology 

    Kilic, H.; Katal, N.S.; Selçuk, Ali Aydın (Institute of Electrical and Electronics Engineers Inc., 2019-09)
    Intrusion Prevention Systems (IPS) and Intrusion Detection Systems (IDS) are the first line of the defense of cyber-environment. This technology is made for capturing and preventing breaches and attacks. Evading of ...
  • Data on cut-edge for spatial clustering based on proximity graphs 

    Aksac, Alper; Özyer, Tansel; Alhajj, Reda (Elsevier B.V., 2020-02)
    Cluster analysis plays a significant role regarding automating such a knowledge discovery process in spatial data mining. A good clustering algorithm supports two essential conditions, namely high intra-cluster similarity ...
  • CACTUS: Cancer image annotating, calibrating, testing, understanding and sharing in breast cancer histopathology 

    Aksac, A.; Özyer, Tansel; Demetrick, D.J.; Alhajj, R. (BioMed Central Ltd., 2020-01)
    Objective: Develop CACTUS (cancer image annotating, calibrating, testing, understanding and sharing) as a novel web application for image archiving, annotation, grading, distribution, networking and evaluation. This helps ...
  • Fuzzy classification methods based diagnosis of parkinson’s disease from speech test cases 

    Dastjerd, N.K.; Sert, O.C.; Özyer, Tansel; Alhajj, R. (Bentham Science Publishers, 2019)
    Background: Together with the Alzheimer’s disease, Parkinson’s disease is considered as one of the two serious known neurodegenerative diseases. Physicians find it hard to predict whether a given patient has already developed ...
  • Analysis and prediction in sparse and high dimensional text data: The case of Dow Jones stock market 

    Sert, Onur Can; Sahin, Salih Doruk; Özyer, Tansel; Alhajj, Reda (Elsevier B.V., 2020-05)
    In this research, we proposed a text analysis system to predict stock market movements using news and social media data. It is a scalable prediction system for sparse and high dimensional feature sets. Using the developed ...
  • Deep learning for financial applications: A survey 

    Özbayoglu, Ahmet Murat; Gudelek, M.U.; Sezer, O.B. (Elsevier Ltd, 2020-08)
    Computational intelligence in finance has been a very popular topic for both academia and financial industry in the last few decades. Numerous studies have been published resulting in various models. Meanwhile, within the ...
  • Unsupervised Fingerprint Classification with Directional Flow Filtering 

    Özbayoğlu, Ahmet Murat (Institute of Electrical and Electronics Engineers Inc., 2019-11)
    In this study, an unsupervised neural network model is proposed for fingerprint classification. The proposed model uses directional flow or local ridge orientation (LRO) information and the relative locations of ...
  • Social Network Analysis to Combat Terrorism: 2015 Paris Attacks 

    Gupta, Animesh; Özyer, Tansel; Rokne, Jon; Alhajj, Reda (Springer, Cham, 2019)
    A series of attacks shook Paris in the year 2015. They were well-coordinated attacks by the terrorist organization ISIL. An in-depth analysis of the attacks is presented in this chapter. This work is divided into several ...
  • Multiuser Precoding for Sum-Rate Maximization in Relay-Aided mmWave Communications 

    Yalçın, Ahmet Zahid; Yapıcı,Y. (Institute of Electrical and Electronics Engineers Inc., 2020-04)
    Relay-aided transmission is envisioned as a key strategy to combat severe path loss and link blockages emerging as unique challenges in millimeter-wave (mmWave) communications. This work considers a relay-aided multiuser ...
  • Social Networks and Surveillance for Society Preface 

    Özyer, Tansel; Bakshi, Sambit; Alhajj, Reda (Springer, Cham, 2019)
    This book focuses on recent technical advancements and state-of-the art technologies for analyzing characteristic features and probabilistic modelling of complex social networks and decentralized online network architectures. ...
  • Evolutionary Optimized Stock Support-Resistance Line Detection for Algorithmic Trading Systems 

    Yildirim, E.O.; Ucar, M.; Özbayoğlu, Ahmet Murat (Institute of Electrical and Electronics Engineers Inc., 2019-11)
    Successful stock traders have been using support-resistance lines for their trading decisions for decades. At the same time, correctly identifying these imaginary lines is one of the greatest challenges that they constantly ...
  • Using Attribute-based Feature Selection Approaches and Machine Learning Algorithms for Detecting Fraudulent Website URLs 

    Aydin, M.; Butun, I.; Bıçakcı, Kemal; Baykal, N. (Institute of Electrical and Electronics Engineers Inc., 2020-01)
    Phishing is a malicious form of online theft and needs to be prevented in order to increase the overall trust of the public on the Internet. In this study, for that purpose, the authors present their findings on the methods ...
  • Financial time series forecasting with deep learning : A systematic literature review: 2005-2019 

    Sezer, Omer Berat; Gudelek, Mehmet Ugur; Özbayoğlu, Ahmet Murat (Elsevier Ltd, 2020-05)
    Financial time series forecasting is undoubtedly the top choice of computational intelligence for finance researchers in both academia and the finance industry due to its broad implementation areas and substantial impact. ...
  • Open-TEE is no longer virtual: Towards software-only trusted execution environments using white-box cryptography 

    Bıçakcı, Kemal; Ak, I.K.; Ozdemir, B.A.; Gozutok, M. (Institute of Electrical and Electronics Engineers Inc., 2019-12)
    Trusted Execution Environments (TEEs) provide hardware support to isolate the execution of sensitive operations on mobile phones for improved security. However, they are not always available to use for application developers. ...
  • A Microprocessor Protection Architecture against Hardware Trojans in Memories 

    Bolat, A.; Cassano, L.; Reviriego, P.; Ergin, Oğuz; Ottavid, M. (Institute of Electrical and Electronics Engineers Inc., 2020-04)
    Software exploitable Hardware Trojan Horses (HWTs) have been currently inserted in commercial CPUs and, very recently, in memories. Such attacks may allow malicious users to run their own software or to gain unauthorized ...

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