# Performance Analysis of a Keyword-Based Trust Management System for Fog Computing
## 2 Related Work
Ensuring these data's security, privacy, and integrity is paramount to protecting patient confidentiality, maintaining trust in health-care systems, and enabling accurate decision-making. However, fog computing environments in health care face unique challenges in achieving trustworthy decision-making. Fog computing, which extends cloud computing capabilities to the edge of the network, brings computation, storage, and networking resources closer to the data sources. While fog computing offers benefits such as reduced latency, improved scalability, and enhanced data privacy, it introduces additional complexities in managing trust and security. The existing literature on trust management in fog computing primarily focuses on general applications and needs a specific focus on the health-care domain. Therefore, a trust management framework tailored to the health-care context must be developed to address health-care systems' particular challenges and requirements. This framework should consider the latest research advancements and provide a comprehensive approach to ensure trustworthy decision-making in health-care environments. The existing literature on trusted fog computing has focused on various aspects of trust management and network optimization. However, there are still gaps that need to be addressed. In this section, we highlight the current state-of-the-art shortcomings and emphasize our proposed framework's unique contributions. The studies presented in [8; 22] made significant strides in trust management in fog computing environments. However, they primarily focus on specific aspects of trust, such as detecting and isolating malicious nodes or providing secure handoff and routing schemes. While these approaches have shown improvements in trustworthiness and security, they must offer a comprehensive framework that addresses the broader challenges of trust management and network performance optimization. Furthermore, existing trust management systems [37; 38; 39; 40; 41; 42; 43] have mainly relied on traditional measures such as reputation, quality of service, and social ties between nodes. While these approaches have provided valuable insights, they often need to pay more attention to fog computing environments' specific requirements and characteristics. Our proposed framework takes a novel approach by introducing a keyword-based trust management system that leverages the unique properties of fog nodes and their interactions. This allows for a more accurate evaluation of trustworthiness and enables the identification of malicious or untrusted nodes before data sharing occurs. Regarding network optimization, previous research has primarily focused on improving latency, packet delivery ratio, and overall performance. However, few studies have explicitly explored the integration of trust management into network optimization techniques. Our proposed framework fills this gap by combining trust management with network performance optimization, creating a holistic approach that enhances security and efficiency in fog computing environments. By incorporating a two-way trust model, our framework enables bidirectional trust relationships between domains, facilitating efficient communication and resource sharing. This novel approach surpasses the limitations of existing one-way trust models, enabling more flexible and secure interactions between fog nodes. In summary, while existing research has made valuable contributions to trust management and network optimization in fog computing, our proposed framework stands out by addressing the limitations of previous approaches. The keyword-based trust management system and two-way trust model offer unique and comprehensive solutions that overcome the shortcomings of current state-of-the-art approaches.