Trust-based mechanism design for cooperative spectrum sensing in cognitive radio networks

Abstract We propose and analyze trust-based cooperative spectrum sensing data fusion schemes against spectrum sensing data falsification attacks in cognitive radio networks. We first consider the case in which a centralized data fusion center is in place for decision making. Then we extend it to the case in which the data fusion center is absent leading to autonomous and distributed decision making. Our trust-based data fusion schemes are based on mechanism design theory to motivate users to report authentic sensing data so as to improve the success rate. Further, we decouple erroneous sensing reports due to low sensing capabilities from false reports due to attacks, thus avoiding unnecessary punishments to good users. We conduct a theoretical analysis validated with extensive simulation and identify optimal parameter settings under which our trust-based data fusion schemes outperform existing non-trust based cooperative spectrum sensing data fusion schemes.