# Modeling Trust in IoT Systems for Drinking-Water Management
## 2 Related Work
These studies underscore the growing significance of AI-driven approaches in mitigating equipment malfunctions and failures, ultimately contributing to improved operational efficiency and reduced downtime in industrial and water management systems. With mounting concerns about IoT system security, the integration of trust management mechanisms has become indispensable. However, it is disconcerting that certain critical industrial sectors, such as drinking-water management, have been overlooked in this endeavor [21]. In the examined previous works, a significant gap has been identified regarding the application of IoT system security principles to drinking-water management. This omission is particularly concerning given the unique characteristics of this domain and the critical stakes associated with the security of water distribution infrastructure. Drinking-water management stands out for its direct impact on public health and safety, necessitating a specific approach to IoT system security. Unlike other industrial sectors, vulnerabilities in drinking-water distribution systems can have immediate and potentially disastrous consequences on the health and well-being of served populations. Therefore, safeguarding these systems must be an absolute priority, underscoring the importance of targeted research focused on IoT system security in this domain. Furthermore, the complexity of drinking-water distribution networks, coupled with the sensitivity of the data and processes involved, requires tailored security approaches. IoT systems in this context must not only protect digital data but also ensure the reliability and integrity of the physical processes associated with water distribution. This dual requirement makes security challenges in this domain particularly intricate and deserving of specific attention from the research community. The previous works have inadequately addressed the specificities of drinking-water management in the context of IoT system security. This gap underscores the urgent need for targeted research aimed at developing adapted and effective security approaches to protect critical water distribution infrastructure against cyber threats and security breaches. To address this gap, we propose an innovative approach. By meticulously evaluating trust among critical elements, we aim to establish robust trust relationships, fostering secure collaboration between IoT devices, control systems, and qualified personnel. Our approach endeavors to mitigate risks by identifying trust levels, therefore providing a solid foundation for proactive threat management in IoT-based water-treatment plants. Through this endeavor, we aspire to fortify the security posture of critical infrastructure and enhance the resilience of water management systems. In reviewing previous works, several trust modeling approaches for the Internet of Things (IoT) have been studied. The approach described in \"A model-driven approach to ensure trust in the IoT\" primarily focuses on trust modeling within the system development lifecycle (SDLC), which may limit its ability to effectively capture and mitigate real-time security risks, particularly in critical environments such as IoT-based water-treatment plants [22]. Similarly, other models, such as the one presented in \"A conceptual trust model for the Internet of Things interactions,\" suffer from limitations related to their generality and abstraction, making it difficult to adapt to the specific needs and security requirements of critical infrastructures like water-treatment plants [23]. Furthermore, approaches like the one described in \"A dynamic trust model in the Internet of Things\" may be limited by their reliance on historical data to predict trust, which can be ineffective in unforeseen situations or against sophisticated attacks [24].