Since the introduction of the Internet of Things (IoT), several researchers have been exploring its productivity to utilize and organize the spectrum assets. Cognitive radio (CR) technology is characterized as the best aspirant for wireless communications to augment IoT competencies. In the CR networks, secondary users (SUs) opportunistically get access to the primary users (PUs) spectrum through spectrum sensing. The multipath issues in the wireless channel can fluster the sensing ability of the individual SUs. Therefore, several cooperative SUs are engaged in cooperative spectrum sensing (CSS) to ensure reliable sensing results. In CSS, security is still a major concern for the researchers to safeguard the fusion center (FC) against abnormal sensing reports initiated by the malicious users (MUs). In this paper, butterfly optimization algorithm (BOA)-based soft decision method is proposed to find an optimized weighting coefficient vector correlated to the SUs sensing notifications. The coefficient vector is utilized in the soft decision rule at the FC before making any global decision. The effectiveness of the proposed scheme is compared for a variety of parameters with existing schemes through simulation results. The results confirmed the supremacy of the proposed BOA scheme in both the normal SUs’ environment and when lower and higher SNRs information is carried by the different categories of MUs.

Internet of Things; cognitive radio network; butterfly optimization algorithm; particle swarm optimization; malicious users; genetic algorithm