Collaborative Spectrum Sensing under Primary User Emulation Attack in Cognitive Radio Networks. Issue 2 (3rd March 2016)

• Record Type: Journal Article
• Authors: Sharifi, Abbas Ali; Sharifi, Morteza; Musevi Niya, Mir Javad
• Is Part Of: IETE journal of research. Volume 62:Issue 2(2016)
• Page Start: 205
• Page End: 211
• Publication Date: 2016-03-03
• Subjects: Attack strength -- cognitive radio -- spectrum sensing -- primary user emulation attack; Electronics -- Periodicals; Telecommunication -- Periodicals; Electronics; Telecommunication; Periodicals; 621.38
• DOI: 10.1080/03772063.2015.1083907
• Languages: English
• ISSNs: 0377-2063

Abstract

ABSTRACT: Spectrum sensing is the main function of cognitive radio (CR), which enables the CR users to detect the spectrum holes. Inherent characteristics of CR have imposed some serious threats to the networks. One of the common threats in CR network is primary user emulation attack (PUEA). In this particular type of attack, some malicious users try to imitate primary signal characteristics and defraud CR users to prevent them from accessing the spectrum holes. Therefore, an effective defense strategy is extremely important for robust collaborative spectrum sensing (CSS). The current study introduces a new CSS scheme in the presence of an intelligent PUEA, called attack-aware CSS (ACSS), which is aware of spectrum holes and actually co-located with the licensed primary user (PU) and transmits with the same power level in a way that CR users are not easily able to differentiate between received signal from PU and PUEA. The idea is based on attack strength estimation, where the attack strength is defined as the channel occupancy rate of malicious PUEA which equals to the probability that the malicious emulator occupies a specific spectrum hole. The proposed approach estimates the attack strength and innovatively applies in Neyman–Pearson or likelihood ratio test to improve collaborative sensing performance. Simulation results are provided to indicate the superiority of the proposed ACSS method against PUEA compared with the conventional method.