# Performance Analysis of a Keyword-Based Trust Management System for Fog Computing
## 3 Methodology
### Trusted Management System  
Even if a multilayered fog environment may be considered, we assume a single-layered fog environment for brevity. The proposed approach builds trust using keywords stored in a table in each node. A table is created in each node called the node keywords table. Tables store information on keywords that are assigned to each node. A maximum of 1000 keywords are stored in a table, and when a keyword is used for a short time, it will be replaced using LRU (least recently used approach). Any node will have more than one keyword, and a maximum of four keywords will be assigned. The structure of the table is shown in Table 1.  
Trust Keywords Table Distribution: The distribution and storage of the trust keywords table among fog nodes should be carefully implemented to prevent malicious manipulation. One approach is to employ a decentralized and distributed architecture where each fog node stores a copy of the trust keywords table. This ensures redundancy and mitigates the risk of a single node maliciously keeping a wrong or tampered table. Additionally, mechanisms such as cryptographic techniques can be employed to secure the distribution and storage of the trust keywords table. Trust Establishment: The methodology does not elaborate on how trust is initially established between fog nodes. Trust can be established through various mechanisms, such as a centralized authority that assigns initial trust values to fog nodes based on their reputation or through a decentralized approach where nodes collectively evaluate and assign trust values to each other. The exact mechanism for trust establishment would depend on the specific requirements and design of the trust management system. Trust Evaluation: The methodology mentions that fog client nodes' requests are accepted or rejected based on keyword matching with the available trust keywords table. However, the detailed process of trust evaluation, including how the trust scores are computed and updated, is not provided. Trust evaluation typically involves considering various factors, such as past interactions, behavior analysis, reputation systems, and feedback from other trusted nodes. These factors contribute to the determination of the trustworthiness of a node beyond just keyword matching. Keyword Distribution: The methodology does not describe how the keywords themselves are distributed among the fog nodes. The distribution of keywords can be achieved through various mechanisms, such as predefined keyword assignment during system setup or dynamically assigning keywords based on the node's behavior and interactions. The choice of the keyword distribution mechanism would depend on the specific requirements and characteristics of the trust management system. \begin{table}
\begin{tabular}{c c} \hline \hline
**Fog Nodes** & **Keywords** \\ \hline Node\_1 & A|B|C \\ Node\_2 & D|E|F \\ Node\_3 & K|M|N \\ Node\_N & X|Y|Z \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Keywords for trust management. Each server node shares the keywords table with server nodes within the domain and outside domains. When a fog client node moves to another server node or another domain's server node, the server nodes check the keywords of the requested fog client node with the available keywords table. If the keywords are compared accurately, then the request of the fog client node will be accepted for connectivity or rejected. This way, the server node can identify the untrustworthy client nodes before sharing data. In the same way, the fog client nodes share the trusted server nodes' information with the neighbor's fog client nodes. We assumed that all the connected links were secured for our proposed scheme. Figure 1 presents the proposed trust model in the fog computing environment. It illustrates the domains (Domain A, Domain B, etc. ), the server nodes within each domain, and the mobile fog client nodes connected to them. The figure visually depicts how fog client nodes can move and connect with different server nodes within the same domain or neighboring domains.