Cognitive radio (CR) technology has emerged as a promising solution to alleviate the spectrum scarcity problem. With the capability of sensing the frequency bands in a time and location-varying spectrum environment, CR technology allows an unlicensed user to exploit those frequency bands unused by licensed users in an opportunistic manner. Since different unlicensed users may acquire different channel availability information, they often need to exchange their channel information with each other for the realization of many networking protocols. However, if malicious unlicensed users exchange false channel information among other nodes, the networking protocols may fail, which leads to significant performance degradation. We name this type of attack as the false channel information exchange attack. In this thesis, a distributed algorithm is proposed to identify the malicious nodes and fight against the false channel information exchange attack in CR ad hoc networks. The spatial correlation of the channel information is used to analyze the authenticity of the received channel information. In addition, the temporal correlation of the channel availability is investigated to further enhance the performance. Simulation results show that our proposed algorithm achieves very high detection rate to find out the malicious nodes, while the false alarm rate is relatively low. To the best of our knowledge, this is the first that investigates the false channel information exchange attacks in CR ad hoc networks.