A Semantic Trust Management Model for Wireless Sensor Networks

In today’s era, wireless sensor networks (WSNs) are increasingly prevalent. However, ensuring reliable data delivery is challenging due to the unique characteristics and limited resources of sensor nodes. Malicious nodes can launch internal attacks by injecting false data, jeopardizing WSN integrity. As the Internet of Things (IoT) evolves, reliance on WSNs is expected to increase. A compromised sensor could undermine credibility and accessibility in the sensor layer. Numerous trust management frameworks in academic literature evaluate trust scores among sensors based on communication metrics such as packet forwarding, direct, and indirect communications. In addition, various data trust evaluation models and hybrid models have been proposed. However, these frameworks typically concentrate on assessing a singular type of trust, such as communication or data trust. Moreover, none of the data trust/hybrid models focus on sensor semantics and data correlations to assess the trust score of sensors in WSNs. In this research, we propose a novel semantic trust management (STM) framework for WSNs that integrates both communication and data trust evaluation. Our proposed approach leverages sensor semantics to construct a sensor semantic network, facilitating trust assessment among sensors. Moreover, we comprehensively assess communication and semantic data trust within our trust evaluation framework. Finally, we demonstrate the applicability of our STM framework in real-life WSN applications through a case study on environmental monitoring.