An Intelligent Trust‐Based Approach for Enhanced Sensor Localization in Heterogeneous Wireless Sensor Networks Within IoT Environments

Abstract

Wireless sensor networks (WSNs) enabling the Internet of Things require accurate and secure sensor localization to function reliably. It is important to note that in real‐world deployments, security threats such as false location reporting, Sybil attacks, and falsification of spectrum sensing data continue to significantly degrade localization accuracy and network reliability. The localization of sensors is a fundamental issue in heterogeneous Wireless Sensor Networks (WSNs) in IoT systems, and it needs to be accurate and secure. But current localization methods still have the issues of Primary User Emulation (PUE), Spectrum Sensing Data Falsification (SSDF), Sybil and jamming attacks. In this paper, an intelligent trust‐based localization system which combines multidimensional trust assessment with a modified Artificial Bee Colony (ABC) optimization algorithm for secure routing is proposed. The framework calculates direct and indirect trust scores to detect malicious nodes and to form a trustworthy communication network. The results of the simulations show that the proposed approach has higher packet delivery ratio, higher throughput and lower end‐to‐end delay than the existing approaches. The proposed framework offers a secure, reliable and scalable solution to support heterogeneous IoT enabled WSN applications.