# Privacy-Preserving Solutions in Blockchain-Enabled Internet of Vehicles
## 5 Analysis of Results
The data exchange is next (17.1%). Dynamic navigation (9.8%) and reputation management (7.3%) have some potential and finally general services (7.3%) and advertising (2.4%) complete the areas. As for the privacy types (RQ2), most research papers (86.84%) included in our survey focus on the protection of vehicle identity, known as identity privacy, whereas location (28.95%) and data (31.58%) privacy are almost on the same level as shown in Figure 5. However, many papers simultaneously provide more than one privacy type, as shown in Figure 6, for example, 8 (21%) papers ensure identity and location privacy, 4 (11%) papers identity and data privacy and 3 (8%) papers provide all privacy types. Figure 3: The classification scheme that emerged from the analysis of papers included in this review presented as a mind map. Figure 4: Service areas (RQ1) addressed in the papers included in our review. Figure 5: Privacy types (RQ2) presented in the papers included in our review. Figure 6: Privacy types (RQ2) overlapping using a Venn diagram. Regarding the types of blockchain (RQ3) used per NIST definition [8], 24 (63.16%) of the proposed schemes utilise permissioned blockchain, 8 (21.05%) schemes use permissionless and 4 (10.53%) employ both permissioned and permissionless blockchains. Note that two (5.26%) papers do not specify the type of blockchain they used in their solutions, as shown in Figure 7.  
Although there are many blockchain frameworks (RQ4), Ethereum (15.79%) and Hyperledger Fabric (21.05%) are the ones mostly used by the proposed schemes, as shown in Figure 8, while the majority of the papers (63.16%) do not directly mention any framework. Regarding the privacy mechanisms (RQ5), pseudonyms (52.63%) overwhelm the research papers as shown in Figure 9. Apart from pseudonyms, there are a lot more mechanisms to provide privacy preservation, the most significant ones being zero knowledge proof (15.79%), cloaking/clustering areas (7.89%), access control, homomorphic encryption, ring signatures and CP-ABE; signcrypption and blind signatures shared the same percentage (5.26%). Likewise federating learning, content broadcasting and group signatures shared the same percentage (2.63%). Figure 2:0 Blockchain frameworks (RQ4) presented in the papers included in our review. Figure 2:1 Blockchain types (RQ3) presented in the papers included in our review. Regarding security analysis (RQ6), it is shown in Figure 10 that again most of the proposed solutions are informally analysed (63.16%), where only one solution (2.63%) provides a formal analysis. It is notable that 13 papers (34.21%) do not provide any security analysis. Finally, regarding the maturity level (RQ7), most of the solutions have been tested only in simulation (47.37%) or in experimental environment (31.58%), as shown in Figure 2:2 It is notable that only 4 solutions (10.53%) are proposals, 4 (10.53%) are proof of concept and only 1 (2.63%) is prototype. Figure 2:3 Security analysis (RQ6) provided in the papers included in our review. Figure 2:4 Privacy mechanisms (RQ5) addressed in the papers included in our review.