Abstract
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.
Highlights
Cognitive radio networks (CRNs) are expected to bring evolution to the spectrum scarcity problem through intelligent use of the underutilized or the free spectrum bands [1]
To mitigate the adverse effects caused by secondary users (SUs) mobility pattern, a fusion scheme based on SU’s reputation is proposed
To mitigate the adverse effects caused by SUs mobility pattern, we proposed a new reputation based data fusion (RDF) scheme to provide a better fusion performance
Summary
Cognitive radio networks (CRNs) are expected to bring evolution to the spectrum scarcity problem through intelligent use of the underutilized or the free spectrum bands [1]. The goal of selfish attacker is to monopolize the specific band sneakily by forcing all other SUs to evacuate it; malicious attacker may report absence or presence of the primary user opposite to its actual spectrum sensing results. The goal of this type of attacker is to prevent other SUs from using the spectrum and causing. Considering the practical problems and limitations discussed above, we focus on the issue of secure CSS scheme for mobile CRNs. We proposed the Location-Reports Consistency (LRC) test to filter out inconsistent sensing reports (abnormal sensing value or incorrect location information) caused by the uncertainty of the noise or the attacker’s malicious behaviors.
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