Journal article
S. Adebo, E. Onwuka, A. Usman, A. Onumanyi
International Journal of Electrical and Computer Engineering (IJECE), 2020
International Journal of Electrical and Computer Engineering (IJECE), 2020
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DOI
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APA
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Adebo, S., Onwuka, E., Usman, A., & Onumanyi, A. (2020). Cooperative-hybrid detection of primary user emulators in cognitive radio networks. International Journal of Electrical and Computer Engineering (IJECE).
Chicago/Turabian
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Adebo, S., E. Onwuka, A. Usman, and A. Onumanyi. “Cooperative-Hybrid Detection of Primary User Emulators in Cognitive Radio Networks.” International Journal of Electrical and Computer Engineering (IJECE) (2020).
MLA
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Adebo, S., et al. “Cooperative-Hybrid Detection of Primary User Emulators in Cognitive Radio Networks.” International Journal of Electrical and Computer Engineering (IJECE), 2020.
BibTeX Click to copy
@article{s2020a,
title = {Cooperative-hybrid detection of primary user emulators in cognitive radio networks},
year = {2020},
journal = {International Journal of Electrical and Computer Engineering (IJECE)},
author = {Adebo, S. and Onwuka, E. and Usman, A. and Onumanyi, A.}
}
Abstract
Primary user emulator (PUE) attack occurs in Cognitive Radio Networks (CRNs) when a malicious secondary user (SU) poses as a primary user (PU) in order to deprive other legitimate SUs the right to free spectral access for opportunistic communication. In most cases, these legitimate SUs are unable to effectively detect PUEs because the quality of the signals received from a PUE may be severely attenuated by channel fading and/or shadowing. Consequently, in this paper, we have investigated the use of cooperative spectrum sensing (CSS) to improve PUE detection based on a hybrid localization scheme. We considered different pairs of secondary users (SUs) over different received signal strength (RSS) values to evaluate the energy efficiency, accuracy, and speed of the new cooperative scheme. Based on computer simulations, our findings suggest that a PUE can be effectively detected by a pair of SUs with a low Root Mean Square Error rate of 0.0047 even though these SUs may have close RSS values within the same cluster. Furthermore, our scheme performs better in terms of speed, accuracy and low energy consumption rates when compared with other PUE detection schemes. Thus, it is a viable proposition to better detect PUEs in CRNs.
