Drs. Kemal Akkaya and Selcuk Uluagac

Today’s vehicles are becoming cyber-physical systems that not only communicate with other vehicles but also gather information from hundreds of sensors within them. These developments help create smart and connected self-driving vehicles that will introduce significant information to drivers, manufacturers, insurance companies and maintenance service providers for various applications. One such application that is becoming crucial with the introduction of self-driving cars is the forensic analysis of traffic accidents. The utilization of vehicle-related data can be instrumental in post-accident scenarios to discover the party at fault, particularly for self-driving vehicles. With the opportunity of being able to access various information in cars, in this project we propose a permissioned blockchain framework among the various elements involved to manage the collected vehicle-related data. Specifically, we will first integrate vehicular public key infrastructure (VPKI) to the proposed blockchain to provide membership establishment and privacy. Next, we will design a fragmented ledger that will store detailed data related to vehicles such as maintenance information/history, car diagnosis reports and so on. The proposed forensic framework enables trustless, traceable and privacy-aware post-accident analysis with minimal storage and processing overhead.