QoS-Aware Decentralized Trustworthy Forensic Evidence Management Framework Using the Internet of Vehicle Things (IoVT)

Vehicles are becoming physical computer systems that connect with other cars and collect data from numerous pieces of equipment. These improvements contribute to developing smart and connected automobiles that will supply valuable data to owners, producers, insurance firms, and repair network operators for various uses. In post-accident circumstances, especially for auto vehicles (self-driving cars), using transportation data might help identify the guilty party. Verification, accessibility, secrecy, and dependability are all privacy needs for a vehicular ad hoc network. These criteria are linked to critical attacks that make operating a network difficult. However, to access different types of information in automobiles, we proposed a permissioned blockchain framework to organize the acquired transportation information among the numerous parts concerned. We incorporate the public key exchange protocol on the vehicle into the projected blockchain-based forensic system to ensure participation identification and anonymity. The proposed system offers a deep learning-based predictive incident modeling with blockchain for the incident data stored in the blockchain. Moreover, several methods have been combined in forensic management with blockchain to establish an auto-evaluation scheme. As a result, we extensively evaluated, analyzed, and discussed the works and contributions of skilled researchers to uncover new avenues in an ongoing and prospective study. The main goal of this research might be to explore the future potential for smart and connected automobiles using blockchain.