Improved soft fusion-based cooperative spectrum sensing defense against SSDF attacks

Abstract

In the cognitive radios (CR), there is a security issue-spectrum sensing data falsification attacks (SSDF) in the process of cooperation. Some malicious users (MUs) who unwilling to cooperate friendly with other users may launch SSDF attacks by falsifying their local sensing information sent to fusion center (FC) intentionally, result in interfering with the detection and threat the CR networks. In order to defense against the SSDF attacks, an improved soft fusion-based algorithm is given in this paper, the key idea of the algorithm is that the cooperation is viewed as a service-evaluation process and making use of cognitive users' (CUs) average reputation degrees to reflect the service quality, then allocate properly the CUs' weights in the fusion according to the reputation degrees. Simulation results show that the sensing performance of the improved algorithm is better than the traditional soft-fusion CSS in the presence of SSDF attacks.