Detection of primary user emulation attack based on modified adaptive orthogonal matched pursuit for cognitive radio networks in HCRAN
Lilly Abau Yosia Odwa, Yueyun Chen, Zhiyuan Mai · Proceedings of the ACM Turing Celebration Conference - China · 2019
Nowadays, it has been reported by researchers that the biggest spectrum assignment problem is not scarcity of radio resources, but rather spectrum utilization. Cognitive radio (CR) emerges as a potential candidate to increase spectral efficiency. However, for a single CR to accurately detect the activity state of PUs, many factors have made it hard. Therefore, Cooperate Spectrum Sensing (CSS) has been introduced to improve detection performance; but this introduces security problem due to the presence of malicious attackers; which can be for instance incumbent emulation by Primary User Emulation Attacker (PUEA). In this paper, A Modified Advanced Orthogonal Matching Pursuit (MAOMP) is proposed to detect the presence of PEUA in a CR network based on locations of the users. Restricted Issometry Property (RIP) is used to evaluate the performace. This paper presents a fast, accurate and efficient approach to detect PUEAs present in the network.