Securing IoT Delay-Sensitive Communications with Opportunistic Parallel Transmission Capability

The futuristic perception of the Internet of Things (IoT) comprises of billions of interconnected devices that can be positioned almost anywhere, starting from our own bodies to the most distant locations on the globe. Within this setup, the massive number of nodes will be competing for bandwidth. To alleviate the expected spectrum scarcity problem in IoT applications, cognitive radio (CR) technology is proposed. In CR-IoT applications, IoT nodes share the idle channels owned by the primary users (PUs). Hence, efficient channel-assignment algorithms are needed to allow CR devices access to the spectrum without interfering with the PUs. Additionally, as these devices become more intrusive in our daily lives, security concerns are escalating. Thus, addressing CR-IoT security threats is now becoming crucial. One of these security threats is jamming which may result in disrupting data transmission between CR- IoT devices. In this paper, we propose a probabilistic-based multi-channel assignment algorithm that considers primary user activity, channel conditions, jamming attack levels, and data-rate requirements to provide spectrally efficient data transmission between CR-IoT nodes subject to delay constraints. The algorithm is verified using the open large-scale Future Internet-of-Things (FIT) IoT-LAB testbed. Practical results show that our proposed algorithm is capable of enhancing network performance without requiring additional network resources or power.