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Title: Detection performance and mitigation techniques in CR networks
Author: Ammar, Mahmod
ISNI:       0000 0004 6495 3775
Awarding Body: University of Hull
Current Institution: University of Hull
Date of Award: 2017
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Pervasive wireless communications rely enormously on spectrum utilization; the increase in demand for new wireless services and their application has led to spectrum scarcity. Spectrum limitations can be resolved by cognitive radio (CR) which is a technology that allows secondary users (SUs) to use the spectrum when it is not occupied by primary users (PUs). In this thesis, the security issues that decrease CR performance are discussed; there are two major threats i.e. primary user emulation attack (PUEA) and spectrum sensing data falsification attack (SSDF). Firstly, the CR network (CRN) is simulated whereby PUs and SUs are presented in the system with the presence of multiple malicious users that are randomly located within a circle of radius (R). The simulation results, based on an analytical model, show that the false alarm probability is significantly affected by the network radius Rand malicious users' number, and it is proved that there is a range of R over which the PUEAs are most successful. Secondly, a transmitter verification scheme (direct scheme) and indirect trust scheme that considers the users' history are presented; the results proved that if the signal to noise ratio (SNR) is raised, correspondingly the t:rnstworthiness of the PU is considerably increased. Based on these two schemes, the trnstworthiness of the PU is much higher than that of the malicious user and because the indirect scheme considers the historical behaviour of the user, it improves the user's trustworthiness. Finally, cooperative spectrum sensing (CSS) approaches are proposed, namely, a trust based approach, a punishment based approach and a dedicated punishment based approach. It is proved that these proposed CSS approaches outperform the traditional majority scheme despite a high number of malicious users. In addition, the dedicated punishment approaches which punish only the malicious users outperform the other approaches.
Supervisor: Riley, N. G. ; Paulson, Kevin S. Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: Engineering