## 1 Introduction  
The advent of the Internet of Things (IoT) [1; 2] has ushered in an era of unprecedented connectivity and inter-device communication, revolutionising industries ranging from healthcare to transportation. As IoT ecosystems continue to proliferate along with new communication protocols [3], the need for robust security and trust mechanisms becomes increasingly imperative. The vulnerabilities associated with the vast network of interconnected devices raise concerns about data integrity, privacy, and unauthorised access [4; 5; 6; 7]. In particular, the exponential growth of IoT deployments has brought forth a multitude of security concerns, including the risk of eavesdropping, data tampering, and unauthorised access. Traditional security measures often fall short in dynamically evolving IoT environments, necessitating innovative solutions to fortify these networks.  
Given the premises above, our research aims to establish a resilient framework for secure communication over extended distances within IoT deployments. In particular, we investigated the efficacy of the Meshtastic protocol in conjunction with the LoRaWAN communication technology ([[https://lora-alliance.org/](https://lora-alliance.org/)]([https://lora-alliance.org/](https://lora-alliance.org/))) in securing and enhancing trust in IoT networks.  
Meshtastic [8] is a dynamic mesh networking solution designed to provide adaptability to the dynamic nature of IoT deployments. The LoRaWAN [9; 10] networking protocol allows IoT devices to operate in regional, national or global networks by satisfying basic Internet of Things requirements: bi-directional communication, end-to-end security, mobility, and localisation services.  
By leveraging the strengths of Meshstastic's dynamic mesh networking capabilities and LoRa's low-power, long-range communication, we designed an integrated approach to mitigate common security threats prevalent in IoT environments. Indeed, Meshstastic's adaptability is complemented by LoRa's efficiency, offering a solution that not only enhances security but also addresses the power constraints often associated with IoT devices. In particular, we designed the integration of a specific reputation model within the Meshstastic protocol. The reputation model was originally developed by some of the authors of this manuscript for a generic set of IoT devices. We developed a particular, customised version to integrate the model itself into the Meshstastic protocol. The integration has been tested in a few experiments to obtain a set of experimental results that validate our approach. The integrated approach presented in this paper contributes to the ongoing discourse on securing IoT networks, providing a pathway for researchers, industry practitioners, and policymakers to fortify the foundation of trust in expanding the IoT landscape. The integrated approach of the Meshtastic protocol with LoRa technology in IoT environments offers a wide range of potential real-world applications due to its enhanced security, energy efficiency, and adaptability, such as Industrial IoT (IIoT), environmental monitoring, supply chain management, and disaster management. Overall, the integration of the Meshtastic protocol with our reputation model opens up a plethora of opportunities for enhancing security, reliability, and efficiency in various IoT applications across different sectors.  
This manuscript is organised as follows: Section 2 discusses the main related works. Section 3 introduces details of the Meshtastic protocol, which was useful in enabling the integration of the reputation model. Section 4 explains the design of the original reputation model previously developed by some of the authors of this manuscript, while Section 5 explains the design of the specific reputation model integrated into the protocol. Section 6 provides details of the simulations performed to validate our approach and, finally, in Section 7, we draw our conclusions.