Security-aware channel assignment in IoT-based cognitive radio networks for time-critical applications

Abstract

Cognitive radio networks (CRNs) have a great potential in supporting time-critical data delivery among the Internet of Things (IoT) devices and for emerging applications such as smart cities. However, the unique characteristics of different technologies and shared radio operating environment can significantly impact network availability. Hence, in this paper, we study the channel assignment problem in time-critical IoT-based CRNs under proactive jamming attacks. Specifically, we propose a probabilistic spectrum assignment algorithm that aims at minimizing the packet invalidity ratio of each cognitive radio (CR) transmission subject to delay constrains. We exploit the statistical information of licensed users' activities, fading conditions, and jamming attacks over idle channels. Simulation results indicate that network performance can be significantly improved by using a security- availability- and quality-aware channel assignment that provides communicating CR pair with the most secured channel of the lowest invalidity ratio.