WIDE: A witness-based data priority mechanism for vehicular forensics

Abstract

In this paper, we present a WItness based Data priority mEchanism (WIDE) for vehicles in the vicinity of an accident to facilitate liability decisions. WIDE evaluates the integrity of data generated by these vehicles, called witnesses, in the event of an accident to assure the reliability of data to be used for making liability decisions and ensure that such data are received from credible witnesses. To achieve this, WIDE introduces a two-level integrity assessment to achieve end-to-end integrity by initially ascertaining the integrity of data-producing sensors, and validating that data generated have not been altered on transit by compromised road-side units (RSUs) by executing a practical byzantine fault tolerance (pBFT) protocol to reach consensus on data reliability. Furthermore, WIDE utilises a blockchain based reputation management system (BRMS) to ensure that only data from highly reputable witnesses are utilised as contributing evidence for facilitating liability decisions. Finally, we formally verify the proposed framework against data integrity requirements using the Automated Verification of Internet Security Protocols and Applications (AVISPA) with High-Level Protocol Specification Language (HLPSL). Qualitative arguments show that our proposed framework is secured against identified security attacks and assures the reliability of data utilised for making liability decisions, while quantitative evaluations demonstrate that our proposal is practical for fully autonomous vehicle forensics.