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Primary User Emulation and Jamming Attack Detection in Cognitive Radio via Sparse Coding

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Document pages: 19 pages

Abstract: Cognitive radio is an intelligent and adaptive radio that improves theutilization of the spectrum by its opportunistic sharing. However, it isinherently vulnerable to primary user emulation and jamming attacks thatdegrade the spectrum utilization. In this paper, an algorithm for the detectionof primary user emulation and jamming attacks in cognitive radio is proposed.The proposed algorithm is based on the sparse coding of the compressed receivedsignal over a channel-dependent dictionary. More specifically, the convergencepatterns in sparse coding according to such a dictionary are used todistinguish between a spectrum hole, a legitimate primary user, and an emulatoror a jammer. The process of decision-making is carried out as a machinelearning-based classification operation. Extensive numerical experiments showthe effectiveness of the proposed algorithm in detecting the aforementionedattacks with high success rates. This is validated in terms of the confusionmatrix quality metric. Besides, the proposed algorithm is shown to be superiorto energy detection-based machine learning techniques in terms of receiveroperating characteristics curves and the areas under these curves

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