A Byzantine attack defender: The Conditional Frequency Check

Collaborative spectrum sensing is vulnerable to the Byzantine attack. Existing reputation based countermeasures will become incapable when malicious users dominate the network. Also, there is a scarcity of methods that fully explore the Markov property of the spectrum states to restrain sensors' statistical misbehaviors. In this paper, a new malicious user detection method based on two proposed Conditional Frequency Check (CFC) statistics is developed with a Markovian spectrum model. With the assistance of one trusted sensor, the proposed method can achieve high malicious user detection accuracy in the presence of arbitrary percentage of malicious users, and thus significantly improves collaborative spectrum sensing performance.