Securing Delay-Sensitive CR-IoT Networking Under Jamming Attacks: Parallel Transmission and Batching Perspective
Haythem Bany Salameh, Mohammad M. Al-Quraan · IEEE Internet of Things Journal · 2020
Cognitive radio (CR) is envisioned as an enabling technology for the Internet-of-Things (IoT) networking by providing spectrum opportunities to the huge number of communicating IoT devices (the so-called CR-IoT networking). Due to the nature of its wireless operating media, CR-IoT networks are vulnerable to jamming attacks. In CR-IoT networks with delay-sensitive applications, such attacks can incur longer packet transmission delay, resulting in received obsolete packets and service unavailability. Therefore, an important challenge in this domain is how to perform a secured channel assignment that can provide soft guarantees on the timeline of the packet delivery while satisfying a predefined Quality-of-Service (QoS) requirements. In this article, we propose a security-aware batch-based MAC protocol for delay-sensitive CR-IoT networks that attempts at improving the network performance by exploiting the parallel transmission capabilities of the CR-IoT devices while being jamming aware. Our protocol performs simultaneous assignment decisions for contending CR-IoT devices. Specifically, we formulate the channel assignment problem that attempts at maximizing the number of served CR-IoT users subject to user-rate demand, number of transceivers per CR-IoT device, and delay (packet invalidity) constraints as an optimization problem. This problem is shown to be a binary linear programming problem, which is, in general, NP-hard. Hence, we use a sequential fixing linear programming technique, which provides a near-optimal solution. To implement our channel assignment in a distributed manner, we adopt an access window (AW)-based access protocol that allows the users to exchange their control information and conduct the spectrum assignment. Compared to reference protocols, simulation results show that our protocol significantly improves spectrum efficiency and CR-IoT network performance.