Reputation Aware Collaborative Spectrum Sensing for Mobile Cognitive Radio Networks

Abstract

The task of spectrum sensing for Dynamic Spectrum Access in Cognitive Radio Networks (CRNs) is very challenging in the presence of malicious secondary users that may launch Spectrum Sensing Data Falsification (SSDF) attacks. Existing solutions to detect such malicious behaviors cannot be utilized in scenarios where the transmission range of primary users is limited within a small sub-region of the CRN, such as low-power primary user devices like wireless microphones or emergency warning systems for vehicles. In this paper, we present a reputation system that works in the scenarios described above in conjunction with a semi-supervised spatio-spectral anomaly/outlier detection system. This system guarantees protection of incumbent primary users' communication rights while at the same time making optimal use of the spectrum when it is not used by primary users. Simulation of our proposed scheme under typical network conditions and SSDF attack shows that spectrum decision error rate is reduced to be less than 2% and detection rate of malicious secondary users is up to 95%.