## 3 Auto-Insurance Systems Based on Cloud or Blockchain
### Blockchain-Based Auto-Insurance Applications and Frameworks
It used anonymous certificates to provide pseudonymity for a specified period of time. The ubiquitous set of connected automated vehicles (CAVs) used automotive sensors and communications to collect data to establish indisputable claims and send them to third parties. Direct communication without the involvement of a third party is always considered more secure. A mobile application called Dia-LOG presented in [34] enables communication between vehicles and authorized devices to collect transactions, and provides integrity and data protection to support digital forensic investigations. Dia-LOG is a reliable and secure privacy protection mechanism that effectively creates an automotive logging system specifically for forensic data collection and storage. Endpoint detection and response (EDR) is recommended as a way to capture data after authentication using a personal mobile device while accessing recorded data. Despite this solution, it is clear that analyzing raw controller area network (CAN) messages requires the reverse engineering of message syntax and semantics, the reconstruction of vehicle dynamics, and the decontextualization of messages and their content. This requires the manual inspection of large amounts of data. In the event of an accident, EDR stores vehicle data for investigation purposes. Investigators also use forensic data loggers that continuously store vehicle data, such as speed and accelerometer readings. Another traffic accident investigation system was proposed in [35], which used the digital data generated by numerous sensors in a vehicle. The authors adopted blockchain-based technology to investigate traffic incidents in self-driving vehicles. They mentioned that it is difficult to evaluate the data in terms of video analysis, because drivers may damage the video, the recording may not be complete, or the driver may refuse to collect it. The use of the unique information provided by sensors, as well as digital forensics analyses with data integrity, could help to overcome the analytical challenges created by poor video quality. A witness-based data priority mechanism (WIDE) was introduced by [PERSON] et al. [36] for vehicles in the vicinity of an accident. As soon as an accident occurs, WIDE assesses the integrity of the data produced by vehicles (referred to as witnesses) to ensure the trustworthiness of the information that will be utilized to determine the liability of each driver. In the WIDE model, a two-level integrity assessment is used, which first verifies the reliability of the sensors that provide the data before ensuring that the data are not changed during transit. It also prioritizes witness data and ensures that only the most reliable witness information is used. A blockchain-based architecture for the vehicle insurance sector was presented in [37], which manages and automates the claims payment process. The proposed car insurance policy model (CAIPY) was an ecosystem for vehicle insurance. This model was based on the IPFS and blockchain-based infrastructure of the vehicle insurance sector, which makes insurance claims transparent and tamper-proof using Ethereum smart contracts. Smart contracts can assist parties in establishing the required trust by safeguarding the contract inside a blockchain [38]. The physical insurance policies between consumers and insurers served as a model for the pieces used in the creation of CAIPY. To store vehicle health information, smart contracts are installed separately and communicate with sensors. In addition to auto-insurance, many blockchain models have been proposed to deal with insurance fraud in the health sector. A blockchain-based application [39] was developed to improve current health insurance business practices. The technique aimed to detect fraud in health insurance using data collected from all insurance firms [40]. Amazon Web Services (AWS) and BigchainDB were used to create a blockchain system wherein MongoDB stored the blocks in each node of BigchainDB.