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dc.contributor.authorFurqan, Haji Muhammad
dc.contributor.authorAygül, Mehmet Ali
dc.contributor.authorNazzal, Mahmoud
dc.contributor.authorArslan, Hüseyin
dc.date.accessioned2020-08-06T06:18:26Z
dc.date.available2020-08-06T06:18:26Z
dc.date.issued2020en_US
dc.identifier.citationFurqan, H. M., Aygül, M. A., Nazzal, M. ve Arslan, H. (2020). Primary user emulation and jamming attack detection in cognitive radio via sparse coding. Eurasip Journal on Wireless Communications and Networking, 2020(1). https://dx.doi.org/10.1186/s13638-020-01736-yen_US
dc.identifier.issn1687-1472
dc.identifier.issn1687-1499
dc.identifier.urihttps://dx.doi.org/10.1186/s13638-020-01736-y
dc.identifier.urihttps://hdl.handle.net/20.500.12511/5678
dc.description.abstractCognitive radio is an intelligent and adaptive radio that improves the utilization of the spectrum by its opportunistic sharing. However, it is inherently vulnerable to primary user emulation and jamming attacks that degrade the spectrum utilization. In this paper, an algorithm for the detection of primary user emulation and jamming attacks in cognitive radio is proposed. The proposed algorithm is based on the sparse coding of the compressed received signal over a channel-dependent dictionary. More specifically, the convergence patterns in sparse coding according to such a dictionary are used to distinguish between a spectrum hole, a legitimate primary user, and an emulator or a jammer. The process of decision-making is carried out as a machine learning-based classification operation. Extensive numerical experiments show the effectiveness of the proposed algorithm in detecting the aforementioned attacks with high success rates. This is validated in terms of the confusion matrix quality metric. Besides, the proposed algorithm is shown to be superior to energy detection-based machine learning techniques in terms of receiver operating characteristics curves and the areas under these curves.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectCognitive Radioen_US
dc.subjectJamming Detectionen_US
dc.subjectMachine Learningen_US
dc.subjectPhysical Layer Securityen_US
dc.subjectPrimary User Emulation Detectionen_US
dc.subjectResidual Componentsen_US
dc.subjectSparse Codingen_US
dc.subjectAuthenticationen_US
dc.subjectPhysical Layer Authenticationen_US
dc.titlePrimary user emulation and jamming attack detection in cognitive radio via sparse codingen_US
dc.typearticleen_US
dc.relation.ispartofEurasip Journal on Wireless Communications and Networkingen_US
dc.departmentİstanbul Medipol Üniversitesi, Mühendislik ve Doğa Bilimleri Fakültesi, Elektrik ve Elektronik Mühendisliği Bölümüen_US
dc.authorid0000-0002-7094-8521en_US
dc.authorid0000-0003-3375-0310en_US
dc.authorid0000-0001-9474-7372en_US
dc.identifier.volume2020en_US
dc.identifier.issue1en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.identifier.doi10.1186/s13638-020-01736-yen_US
dc.identifier.wosqualityQ3en_US
dc.identifier.scopusqualityQ2en_US


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