Cryptology ePrint Archive: Report 2020/011

BB-VDF: Enabling Accountability and Fine-grained Access Control for Vehicular Digital Forensics through Blockchain

Ming Li,Jian Weng, Jia-Nan Liu, Xiaodong Lin, 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 and determining evidences 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 fine-grained data access control in VDF is a non-trivial challenge. To mitigate this issue, in this paper, we propose a blockchain-based scheme for VDF named BB-VDF, in which the accountable protocols and privacy preservation methods are constructed. The desirable security properties and fine-grained data access control are achieved based on the customized smart contracts and cryptographic constructions. Specifically, we design novel smart contracts that model the forensics procedures as a finite state machine, which guarantees accountability that each participant performs auditable cooperation under tamper-resistant and traceable transactions. Furthermore, we design a distributed key-policy attribute based encryption scheme with partially hidden access structures to realize the secure fine-grained forensics data access control. Systematic security analysis and extensive experimental results show the feasibility and practicability of the proposed BB-VDF scheme.

Category / Keywords: cryptographic protocols / Vehicular digital forensics, blockchain, accountability, fine-grained, privacy preservation.

Date: received 5 Jan 2020, last revised 6 Jan 2020

Contact author: limjnu at gmail com

Available format(s): PDF | BibTeX Citation

Version: 20200106:141103 (All versions of this report)

Short URL: ia.cr/2020/011


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