Trust-based data fusion mechanism design in cognitive radio networks

Cognitive radio is a promising solution for spectrum scarcities in the future. Secondary users (SUs) adopt cooperative sensing to learn the primary user´s (PU´s) occupancy activity. This paper develops a trust-based data aggregation scheme to cope with malicious SU attack in cooperative spectrum sensing in cognitive radio networks. The proposed scheme combines the first-hand and second-hand sensing evidence to guarantee the overall performance and adopts a static game model to discourage malicious SUs from reporting fake detection parameters. Both theoretical and simulation results show that the proposed scheme outperforms the traditional majority aggregation scheme despite a high percentage of malicious node population and can effectively distinguish malicious nodes from normal nodes by their reputation scores.