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Deep learning-assisted detection of PUE and jamming attacks in cognitive radio systems
(Institute of Electrical and Electronics Engineers Inc., 2020)
Cognitive radio (CR)-based internet of things systems can be considered as an efficient solution for futuristic smart technologies. However, CRs are naturally vulnerable to two major security threats; primary user emulation ...
Deep RL-based spectrum occupancy prediction exploiting time and frequency correlations
(Institute of Electrical and Electronics Engineers Inc., 2022)
In cognitive radio systems, predicting spectrum occupancies is a convenient alternative way to continuous spectrum sensing. It can provide information on spectrum usage and so empty spectrum bands can be used by secondary ...
Primary user emulation and jamming attack detection in cognitive radio via sparse coding
(Springer, 2020)
Cognitive 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 ...
Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models
(MDPI, 2021)
In cognitive radio systems, identifying spectrum opportunities is fundamental to efficiently use the spectrum. Spectrum occupancy prediction is a convenient way of revealing opportunities based on previous occupancies. ...