Block4Forensic: An Integrated Lightweight Blockchain Framework for Forensics Applications of Connected Vehicles (1802.00561v2)

Abstract: Today's vehicles are becoming cyber-physical systems that do not only communicate with other vehicles but also gather various information from hundreds of sensors within them. These developments help create smart and connected (e.g., 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 for traffic accidents. The utilization of vehicle-related data can be instrumental in post-accident scenarios to find out the faulty party, particularly for self-driving vehicles. With the opportunity of being able to access various information on the cars, we propose a permissioned blockchain framework among the various elements involved to manage the collected vehicle-related data. Specifically, we first integrate Vehicular Public Key Management (VPKI) to the proposed blockchain to provide membership establishment and privacy. Next, we design a fragmented ledger that will store detailed data related to vehicle such as maintenance information/history, car diagnosis reports, etc. The proposed forensic framework enables trustless, traceable and privacy-aware post-accident analysis with minimal storage and processing overhead.

• The paper proposes a permissioned blockchain model integrating VPKI and a fragmented ledger to enhance vehicular data management in forensic investigations.
• It employs a lightweight design to reduce storage and processing demands while ensuring traceable, privacy-conscious post-accident analyses.
• The framework balances detailed data logging with robust privacy measures, offering a reliable solution for forensic attribution in connected and autonomous vehicles.

An Overview of "Block4Forensic: An Integrated Lightweight Blockchain Framework for Forensics Applications of Connected Vehicles"

Communication and data integration among connected vehicles have transformed them into complex cyber-physical systems. These advancements necessitate new approaches to address challenges related to data privacy, security, and forensic analysis, particularly in scenarios involving traffic accidents. The paper "Block4Forensic: An Integrated Lightweight Blockchain Framework for Forensics Applications of Connected Vehicles" addresses these needs by proposing a novel framework utilizing blockchain technology.

This research introduces a permissioned blockchain model designed to manage vehicular data in forensic applications. The primary aim is to aid in post-accident investigations, especially where self-driving technologies are involved, by establishing a more reliable and efficient system for determining culpability. The proposed framework is notable for incorporating Vehicular Public Key Management (VPKI) to ensure privacy and facilitate membership management within the blockchain network.

The architectural innovation includes a fragmented ledger system that stores detailed vehicle data, such as maintenance history and diagnostic reports. The use of a fragmented ledger seeks to reduce the inherent storage and processing demands typically associated with traditional blockchain implementations, making the system lightweight and scalable.

One of the essential attributes of this framework is its capacity to deliver trustless, traceable, and privacy-conscious forensic analyses. The integration of VPKI provides a robust mechanism that balances the need for access to detailed vehicular data with the imperative to preserve user privacy. This balance is critical, given the sensitivity of the data involved and the broad range of stakeholders, including drivers, manufacturers, insurers, and maintenance service providers, who may access the information.

The implications of this research are significant for both theoretical exploration and practical application in the field of connected vehicle technology. The integration of blockchain solutions into vehicular networks could pave the way for more secure and trustworthy handling of data, potentially becoming a staple in scenarios requiring transparent and immutable data logging. Furthermore, as connected and autonomous vehicles become more prevalent, the challenges around data management and privacy will intensify, making frameworks such as Block4Forensic pivotal.

This paper contributes to advancing the discourse on connected vehicle technologies, offering a pathway towards more reliable, efficient, and privacy-aware forensic solutions. Future developments in this area could explore further optimization of blockchain architectures to cater to broader data applications and piloting real-world implementations to validate theoretical predictions. The continued exploration of blockchain technology in vehicular networks holds promise for enhancing the safety and accountability of emerging automotive technologies.