A Secure Cooperative Spectrum Sensing Scheme in Mobile Cognitive Radio Networks
Author(s) -
Jun Du,
Daoxing Guo,
Bangning Zhang,
Ligang Shang
Publication year - 2014
Publication title -
international journal of distributed sensor networks
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.324
H-Index - 53
eISSN - 1550-1477
pISSN - 1550-1329
DOI - 10.1155/2014/620196
Subject(s) - computer science , cognitive radio , false alarm , reliability (semiconductor) , constant false alarm rate , computer network , scheme (mathematics) , real time computing , signal (programming language) , computer security , telecommunications , wireless , algorithm , artificial intelligence , mathematical analysis , power (physics) , physics , mathematics , quantum mechanics , programming language
The reliability of cooperative spectrum sensing (CSS) can be severely degraded by the falsified spectrum sensing reports provided by malicious secondary users (SUs). However, in existing works, the problem of secure CSS in mobile cognitive radio networks (CRNs) has not been well considered yet. The detection of abnormal sensing reports in existing works does not evaluate both sensing reports and locations of SUs simultaneously. And the mobility pattern of all SUs is assumed to be similar, which is impractical in real mobile CRNs. In this paper, spatial correlation of the received signal strength among SUs is exploited to get the evidence whether the received signal strength is consistent with the location from where it is generated. And Dempster-Shafer theory is used to filter out abnormal reports by combining the evidence collected from the spatial correlation algorithm in each sensing period. To mitigate the adverse effects caused by the SUs’ mobility pattern, a fusion scheme based on SUs’ reputation is proposed. In comparison to the existing schemes, simulation results demonstrate that the proposed secure CSS scheme improves the primary user detection rate by 10% at false alarm rate of 0.1 when the mobility pattern of the SUs is different.
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