# Performance Analysis of a Keyword-Based Trust Management System for Fog Computing
## 1 Introduction
The key modules of a fog computing system's design are fog nodes, which might be fog servers called fog service providers or fog clients called fog service requesters [11]. The fog clients include sensors, cars, smartphones, smart watches, cameras, etc. Access points, set-top boxes, street-side devices, gateways, routers, and cellular base stations are a few examples of fog servers [35]. Fog computing offers mobility, geographical dispersion, heterogeneity, location awareness, federation, and interoperability. Cloud computing is not being supplanted by it, and fog computing, in contrast, is replacing it. Fog computing is particularly vulnerable to user privacy and data security breaches due to its features and the flexibility with which it may be implemented. Despite its benefits, several aspects of fog computing, such as its high mobility support, responsiveness, geographical spread, proximity to end users, location awareness, and lack of redundancy, may compromise the security and privacy of the system. In addition to the privacy and security concerns raised by cloud computing, computing in the fog raises new ones. Maintaining trust, which is strongly related to worries about data security and privacy, is one of the issues presented by the fluid environment of fog computing. The definition of trust is the degree of assurance that a person or object will act respectably. The goal of trust management systems in the fog computing environment is to locate and stop the functioning of rogue fog servers that are harmful to clients. Any malicious fog node that behaves like an actual node even though it has been hacked or substituted with a fake one by attackers or malicious users is considered a bad fog node [15]. A rogue fog node is another name for a faulty fog node. A malevolent fog server may covertly gather and utilize user information, provide clients with subpar services, and/or launch assaults. We employ the trust technique to track down rogue fog nodes and security issues in the fog network. The many hurdles and issues related to fog computing are because it is still a relatively new study topic and is still in its infancy stage for building a trustworthy fog environment for Internet of Things (IoT)-based applications [36]. Many researchers have worked on fog computing security, but there are limitations in previous studies. Conventional cryptographic solutions are not appropriate for defending against internal attacks, such as those originating from a malicious fog that has been proven legitimate and included in the system. Existing approaches need to be revised for fog computing for several reasons, including the fact that it requires high mobility support, a dynamic environment, geographical dispersion, position awareness, closeness to end users, and the absence of redundancy, among other factors. Consequently, because trust management guarantees both privacy and security, our contribution to this research is to handle the limitations mentioned above. Many researchers have worked on fog computing security, but there are limitations in previous studies. Conventional cryptographic solutions are not appropriate for being used to defend against internal attacks, such as those originating from a malicious fog that has been proven legitimate and included in the system. Existing approaches are insufficient for fog computing for several reasons, including the fact that it requires high mobility support, a dynamic environment, geographical dispersion, position awareness, closeness to end users, and the absence of redundancy, among other factors. Our contribution to this research is to handle the limitations mentioned above.