Spectrum sensing is the first step to overcome the spectrum scarcity problem in Cognitive Radio Networks (CRNs) wherein all
unutilized subbands in the radio environment are explored for better spectrum utilization. Adversary nodes can threaten these
spectrum sensing results by launching passive and active attacks that prevent legitimate nodes from using the spectrum efficiently.
Securing the spectrum sensing process has become an important issue in CRNs in order to ensure reliable and secure spectrum
sensing and fair management of resources. In this paper, a novel collaborative approach during spectrum sensing process is
proposed. It monitors the behavior of sensing nodes and identifies the malicious and misbehaving sensing nodes. The proposed
approach measures the node’s sensing reliability using a value called belief level. All the sensing nodes are grouped into a specific
number of clusters. In each cluster, a sensing node is selected as a cluster head that is responsible for collecting sensing-reputation
reports from different cognitive nodes about each node in the same cluster. The cluster head analyzes information to monitor and
judge the nodes’ behavior. By simulating the proposed approach, we showed its importance and its efficiency for achieving better
spectrum security by mitigating multiple passive and active attacks.
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