MDS-Based Cloned Device Detection in IoT-Fog Network

The fog-based IoT (IoT-Fog) network, which combines Internet of Things (IoT) and fog computing (FC), has quickly become a key enabler of emerging applications, such as smart transportation, smart homes, and smart grids. It has, however, introduced an IoT device cloning attack, which allows adversaries to mount a range of attacks on IoT networks. IoT devices have a built-in security system, making them an easy target for hackers. Therefore, it is critical to reliably identify and isolate cloned IoT devices to protect IoT networks from adversaries taking control of the network. Existing approaches do not address the problems of compromised device and repeated cloned device simultaneously without requiring the device's exact locations. To this end, we propose a new low complexity IoT device cloning detection approach called maximum distance separable (MDS) which is appropriate for IoT-Fog architecture. We validated the efficiency of MDS analytically and evaluated its performance by comparing it to state-of-the-art approaches in terms of detection rate, communication overhead, memory overhead, and computation overhead. The results indicate that the proposed approach has a very high detection rate, negligible communication and memory overhead, and promising detection time.