Securing real-time opportunistic spectrum access in cognitive networks against malicious secondary users

© 2015 IEEE. 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

Heterogeneous Dynamic Spectrum Access in Cognitive Radio enabled Vehicular Networks Using Network Softwarization

Dynamic spectrum access (DSA) in cognitive radio networks (CRNs) is regarded as an emerging technology to solve the spectrum scarcity problem created by static spectrum allocation. In DSA, unlicensed users access idle channels opportunistically, without creating any harmful interference to licensed users. This method will also help to incorporate billions of wireless devices for different applications such as Internet-of-Things, cyber-physical systems, smart grids, etc. Vehicular networks for intelligent transportation cyber-physical systems is emerging concept to improve transportation security and reliability. IEEE 802.11p standard comprising of 7 channels is dedicated for vehicular communications. These channels could be highly congested and may not be able to provide reliable communications in urban areas. Thus, vehicular networks are expected to utilize heterogeneous wireless channels for reliable communications. In this thesis, real-time opportunistic spectrum access in cloud based cognitive radio network (ROAR) architecture is used for energy efficiency and dynamic spectrum access in vehicular networks where geolocation of vehicles is used to find idle channels. Furthermore, a three step mechanism to detect geolocation falsification attacks is presented. Performance is evaluated using simulation results