Paper 2020/011

Towards Vehicular Digital Forensics from Decentralized Trust: An Accountable, Privacy-preservation, and Secure Realization

Ming Li, Jian Weng, Jia-Nan Liu, Xiaodong Lin, and Charlie Obimbo

Abstract

With the increasing number of traffic accidents and terrorist attacks by modern vehicles, vehicular digital forensics (VDF) has gained significant attention in identifying evidence from the related digital devices. Ensuring the law enforcement agency to accurately integrate various kinds of data is a crucial point to determine the facts. However, malicious attackers or semi-honest participants may undermine the digital forensic procedures. Enabling accountability and privacy-preservation while providing secure data access control in VDF is a non-trivial challenge. To mitigate this issue, in this paper, we propose a blockchain-based decentralized solution for VDF named BB-VDF, in which the accountable protocols and algorithm are constructed. The desirable security properties and fine-grained data access control are achieved based on smart contract and the customized cryptographic construction. Specifically, we design a distributed key-policy attribute based encryption scheme with partially hidden access structures, named DKP-ABE-H, to realize the secure fine-grained forensics data access control. Further, a novel smart contract is designed to model the forensics procedures as a finite state machine, which guarantees accountability that each participant performs auditable cooperation under tamper-resistant and traceable transactions. Systematic security analysis and extensive experimental results show the feasibility and practicability of our proposed BB-VDF scheme.