A Game-Theoretic Approach for Enhancing Security and Data Trustworthiness in IoT Applications

Abstract

Wireless sensor networks (WSNs)-based Internet of Things (IoT) are among the fast booming technologies that drastically contribute to different systems' management and resilience data accessibility. Designing a robust IoT network imposes some challenges, such as data trustworthiness (DT) and power management. This article presents a repeated game model to enhance clustered WSNs-based IoT security and DT against the selective forwarding (SF) attack. Besides, the model is capable of detecting the hardware (HW) failure of the cluster members (CMs), preserving the network stability, and conserving the power consumption due to packet retransmission. The model relies on the TDMA protocol to facilitate the detection process and to avoid collision between the delivered packets at the cluster head (CH). The proposed model aims to keep packets transmitting, isotropic or nonisotropic transmission, from the CMs to the CH for maximizing the DT and aims to distinguish between the malicious CM and the one suffering from the HW failure. Accordingly, it can manage the consequently lost power due to the malicious attack effect or HW malfunction. The simulation results indicate the proposed mechanism improved performance with TDMA over six different environments against the SF attack that achieves the Pareto-optimal DT as compared to a noncooperative defense mechanism.