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Future Internet 2017, 9(4), 79; doi:10.3390/fi9040079

Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System

Information Science and Technology College, Dalian Maritime University, Dalian 116026, China
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Received: 30 September 2017 / Revised: 27 October 2017 / Accepted: 6 November 2017 / Published: 8 November 2017
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Abstract

Collaborative spectral sensing can fuse the perceived results of multiple cognitive users, and thus will improve the accuracy of perceived results. However, the multi-source features of the perceived results result in security problems in the system. When there is a high probability of a malicious user attack, the traditional algorithm can correctly identify the malicious users. However, when the probability of attack by malicious users is reduced, it is almost impossible to use the traditional algorithm to correctly distinguish between honest users and malicious users, which greatly reduces the perceived performance. To address the problem above, based on the β function and the feedback iteration mathematical method, this paper proposes a malicious user identification algorithm under multi-channel cooperative conditions (β-MIAMC), which involves comprehensively assessing the cognitive user’s performance on multiple sub-channels to identify the malicious user. Simulation results show under the same attack probability, compared with the traditional algorithm, the β-MIAMC algorithm can more accurately identify the malicious users, reducing the false alarm probability of malicious users by more than 20%. When the attack probability is greater than 7%, the proposed algorithm can identify the malicious users with 100% certainty. View Full-Text
Keywords: collaborative spectrum sensing; spectrum-sensing false data; β function; feedback iteration; false alarm probability of malicious users collaborative spectrum sensing; spectrum-sensing false data; β function; feedback iteration; false alarm probability of malicious users
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MDPI and ACS Style

Zhang, J.; Cai, L.; Zhang, S. Malicious Cognitive User Identification Algorithm in Centralized Spectrum Sensing System. Future Internet 2017, 9, 79.

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