## 6 Future Research Directions  
Researchers, practitioners, and business experts are always looking for better and more innovative ways to transform the conventional auto-insurance industry into a modern one. They are transforming the entire infrastructure by implementing new and innovative technologies to enhance security, privacy, data management, and storage. In Sections 4 and 5, we discussed the potential issues and possible solutions to these challenges. In the current section, we discuss possible future research directions. 1. No fully reliable methods and frameworks have been proposed or implemented to date for cloud- or blockchain-based auto-insurance systems to ensure the availability of the necessary forensic data. The absence of a reliable dataset can lead to incorrect decisions [27]. Therefore, more research is required from both researchers and insurance organizations to ensure the complete availability of these data without any loss of information. 2. Data security and privacy are key concerns in the auto-insurance sector. \"Cloud services lack data security\" [79]: compared to cloud computing, blockchain technology offers the opportunity to provide secure data transformation using public and private key encryption. Due to the immutable nature of blockchain technology, blockchain-based data exchange can save an insurer the expense of obtaining a public data subscription to reduce fraud. [PERSON] et al., in [79], mentioned that \"implementing blockchain will make data more secure\". Moreover, the study presented in [69] proved that blockchain has the potential to deal with all possible privacy-related threats. More research by academics and insurance firms based on simulations is needed to ensure safe communication in the insurance sector. 3. It is necessary to study and investigate the data storage problem, particularly in blockchain, because data accessibility depends on both private and shared storage. Permanent data storage on every block and the exponential increase in size are the main reasons for the scalability issue [74]; researchers have a responsibility to ensure that a significant amount of secure storage can be provided. 4. Researchers and practitioners should focus on the development of attestation methods and procedures to ensure the precision, dependability, and integrity of the data provided by CAVs as evidence. 5. Encrypting data before storing or uploading them and creating an access policy based on user identity for decryption are standard solutions for data sharing and collaboration. If data are encrypted, they will be unusable, even if leaked to an unauthorized party. Consequently, it is important to recognize and assess the weaknesses and vulnerabilities of encryption algorithms. Increased trust in the cloud, combined with cryptographic approaches, can aid in the implementation of dependable controls, resulting in real business intelligence benefits for stakeholders. Therefore, a suitable encryption technique needs to be developed to meet the privacy requirements [69]. 6. AI, big data, and data-mining techniques can be applied to auto-insurance to handle the various associated challenges, as illustrated in Figure 4. These can be used to monitor user activity in the auto-insurance sector and to keep track of stored data. Auto-insurance companies can benefit from AI by reducing process errors, predicting risks, and identifying fraud [26]. Because of this, the insurance provider will be better able to recommend insurance to customers based on their needs. Consumers can also benefit from enhanced AI-based claims processing. Auto-insurance companies can exploit big data in a variety of ways. For example, telematics provides insurers with the ability to collect information about driver usage and behavior to offer usage-based insurance and premium discounts. Auto-insurance firms can be protected from many types of fraud using big data [27]. For example, prediction models can be used to compare an individual's information to previous fraudulent profiles, facilitating further investigation.