Please use this identifier to cite or link to this item: https://repository.sustech.edu/handle/123456789/16045
Title: Security Model for Wireless Cognitive Radio Network
Other Titles: نمـــوذج أمنـي للشبكـــة الراديوية المعرفيــــة اللاسلكيـــة
Authors: Eltom, Mutaz Mohamed Awad
Supervisor,- Ibrahim Khider Eltahir
Keywords: Communication Engineering
Model for Wireless
Cognitive Radio Network
Issue Date: 10-Mar-2017
Publisher: Sudan University of Science and Technology
Citation: Eltom, Mutaz Mohamed Awad . Security Model for Wireless Cognitive Radio Network / Mutaz Mohamed Awad Eltom ; Ibrahim Khider Eltahir .- Khartoum: Sudan University of Science and Technology, college of Engineering, 2017 .-78p. :ill. ;28cm .- M.Sc.
Abstract: Cognitive Radio (CR) Network is an advanced growing technique and promising technology for the upcoming generation of the wireless networks in order to efficiently utilize the limited spectrum resources and satisfy the rapidly increasing demand for wireless applications and services. Deployment of such networks is hindered by the vulnerabilities that these network are exposed to , this thesis focus on security problems arising from Primary User Emulation (PUE) attack in CR network . The thesis presents a comprehensive introduction to cognitive radio network and the primary user emulation attacks and its impact on CR network. The thesis focus on design a security model using Matlab software and use the Neyman-Pearson Composite Hypothesis Test NPCHT to obtain the hypothesis test and detect the PUE attack . In order to secure CR networks against PUE attacks , the system considered the power received at the secondary receiver. Simulation resulte proved that using the NPCHT it is possible to keep the probability of success of PUE attack low depends on the threshold value. The number of malicious users in the system can significantly increase the probability of false alarm ( successful PUE attack) in the network.
Description: Thesis
URI: http://repository.sustech.edu/handle/123456789/16045
Appears in Collections:Masters Dissertations : Engineering

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