# Security in Wireless Body Sensor Network: A Multivocal Literature Study
## 5 Findings  
Using MLR, we determined the best techniques for securing BSN. After presenting the findings of the MLR scan, we provided a brief description of the materials that were selected. Then, we provided a list of techniques that have been found following MLR data analysis. In February 2022, the investigation was finally concluded. The most recent publications discovered between December 2017 and 2021 were covered in the research. In this study, the selection process included four stages. During the initial screening procedure, 10,871 sources were retrieved from all digital libraries. In the first selection stage 548 sources were selected and in the second stage 433 articles were chosen. Then, in the third selection stage 321 articles and in the fourth selection stage 73 articles were selected. A summary of these findings can be seen in Table 1.  
Table 2 lists the excellency criteria used to evaluate each research. With the following question: \"Is this excellency factor accomplished?\", we used a five-point scale to rate each article (strongly agree, agree, neither agree nor disagree, disagree, and strongly disagree). Some perspectives were provided on the distinctions between scholarly (white) and industrial (grey) literature from the excellency evaluation of the data source. Figure 2 contains the findings of the excellency evaluation for academic and GLR for each standard as a proportion of the relevant overall review of papers. The majority of all ALR articles (91%) explicitly explained their study objective; each one of them categorized the addressed security breaches openly. Additionally, the majority of them (93%) described quite explicitly the security feature offered. Sixty-seven percent of GLR articles are compiled on trusted web pages, but only a portion of the remainder (17%) are not dated. Moreover, around half of the articles (49%) offer background, and 2/3 (67%) analyze the problem discussed by their security mechanism. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Database Resource** & **Initial Search** & **First Stage** & **Second Stage** & **Third Stage** & **Fourth Stage** \\ \hline Science Direct & 1662 & 57 & 57 & 49 & 18 \\ \hline IEEE Xplore & 717 & 62 & 58 & 58 & 16 \\ \hline Wiley & 488 & 39 & 14 & 8 & 5 \\ \hline Scopus & 4425 & 177 & 158 & 136 & 18 \\ \hline Springer & 3245 & 194 & 129 & 48 & 8 \\ \hline ACM Digital Library & 334 & 19 & 17 & 17 & 8 \\ \hline Total & 10,871 & 548 & 433 & 321 & 73 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: MLR search results. \begin{table}
\begin{tabular}{c c} \hline \hline
**EC \#** & **Criteria** \\ \hline \multicolumn{3}{c}{For Academic Literature: conduct the research} \\ \hline EC1 & have well-defined research objectives? \\ \hline EC2 & describe the problem considered by the security solution? \\ \hline EC3 & illustrate the security solution? \\ \hline \multicolumn{3}{c}{For Grey Literature: conduct the study} \\ \hline EC4 & obtained from a trustworthy publishing institution? \\ \hline EC5 & have a clearly stated date? \\ \hline EC6 & present the background where the security solution is used? \\ \hline EC7 & provide the problem addressed by the security solution? \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Excellence criteria for publications. According to the report's results, it can be beneficial and challenging to incorporate GLR into the systematic review since the evidence is based on personal views and experiences. For instance, when describing the research methodology, we may come across lower-quality reports. This must be considered at each stage of the study. Table 3 outlines the information extraction strategy used in this analysis and illustrates the metadata generated for each publication type. A peer review is conducted to ensure accurate results.