Securing Real-Time Opportunistic Spectrum Access in Cognitive Networks against Malicious Secondary Users

Communications in future wireless systems are expected to rely on opportunistic RF spectrum access where unlicensed secondary users either sense RF spectrum to find idle channels or search for idle channels in a geolocation database of idle spectrum. To avoid channel sensing uncertainties, the FCC mandates that secondary users should query geolocation database to find idle channels for given location and time to communicate opportunistically. However, malicious secondary users can fake their geolocations using GPS spoofing techniques to pretend to be in a place where more idle channels are available. In this paper, we implement and investigate how to secure real-time opportunistic spectrum access in cloud based cognitive radio networks (aka ROAR) against malicious secondary users using angle-of- arrival, received signal strength and time-of- arrival. The proposed approach checks the legitimacy of geolocation reported by the secondary users using cloud computing platform before releasing any idle channel information to them to protect licensed primary users. We implement three step detection process to differentiate the legitimate secondary users from malicious ones which help secure ROAR against untrustworthy secondary users. The proposed approach is illustrated through numerical results obtained from both simulations and experiments.