# Blockchain Application in Internet of Vehicles: Challenges, Contributions and Current Limitations
## 3 Review Method
### Reporting the Review  
Based on [30; 32], the goal of this process was to utilize data extraction forms to properly record the information gathered by the authors from the primary study selection. \begin{table}
\begin{tabular}{c c} \hline
**Inclusion Criteria** & **Exclusion Criteria** \\ \hline Peer-reviewed studies & Grey literature \\ Academic theoretical and empirical research & White papers and material from non-academic sources \\ Full-text available & Full-text not available \\ Written in English language & Written in non-English language \\ Published in 2017 onwards & Published before 2017 \\ Relevant to blockchain and IoV concept & Diverged from the field of blockchain and IoV concept \\ Concept addressed by means of a valid methodology & \\ \hline \end{tabular}
\end{table} 
Table 2: Inclusion and exclusion criteria. Figure 3: Procedure for identifying selected studies. For the data extraction process, a framework was formed by the authors using Microsoft Excel. The data extracted from each study were the following:  
* Study details including authorship, year, type of paper, publication location and digital object identifier;
* Summary of the study and description of the observed thematic area;
* Main application area;
* Evaluation of the study in terms of research knowledge including the identified problems;
* Proposed solutions/opportunities, study outcomes and study limitations and/or research directions;
* Evaluation of the study in terms of technological knowledge, including concept validation and blockchain network used. From the considered-studies cluster of 245, the most interesting ones once were selected (excluding the documents in the form of surveys or literature reviews, which were also considered separately), to highlight the main current research trends and the gaps that have yet to be filled. The selection was based on the Interest Tag (i.e., low, medium, high). The authors selected only the studies tagged as \"high\" that were of the highest importance. At this point, it should be stated that the decisions determining whether studies were considered to be of high importance were based on two factors:  
* The study should be sufficiently evaluated in terms of research knowledge;
* The study should be evaluated in terms of technological knowledge. The selected studies are presented in Appendix B, and they are grouped by application area. The following features are highlighted: (a) authors and publication year, (b) application area, (c) identified problems, (d) study outcomes and (e) study limitations and/or research directions. The majority of the studies were high quality conference proceedings and journal articles, although some book chapters were also analyzed. In 2021, the published articles had the highest rank. A clear depiction of the types of publications identified is presented in Figure 4, while the distribution of them within the time range of the review is presented in Figure 5.  
During the analysis process, the authors classified blockchain applications within the IoV into eight main categories according to their purpose and field of activity:  
* Privacy and security;
* Data protection and management;
* P2P energy trading;
* Microgrid management;
* IoV management;
* AI/Machine Learning (ML) and IoV;
* Blockchain performance in the IoV;
* General-purpose studies (e.g., reviews, surveys, etc.). Figure 4: Study types as percentages. The taxonomy of the identified application areas is depicted in Figure 6. The authors found that approximately one in three applications were about Privacy & Security (27%), which included authentication, Vehicle to Everything (V2X) and identity management initiatives. The second most popular category was IoV Management (25.8%). This was followed by P2P Energy Trading and general-purpose studies, accounting for 12.7% and 12.3% of total studies, respectively.