An Enhanced Secure Data Provenance Scheme for the Internet of Vehicles
Anuj Nepal, Robin Doss, Frank Jiang · 2024
Security, privacy preservation, and trust are the most critical requirements for the Internet of Vehicles (IoVs) that rely on a multi-faceted approach. In this paper, we propose a decentralized secure data provenance (SDP) protocol ideal for the dynamic and multi-hop characteristics of the IoVs that leverages Verifiable Credentials (VCs) to attain demonstrable security attributes in terms of privacy, integrity, source identity, and location verification. SDP facilitates privacy and trust for migrated data on different devices and systems. Source authentication and data integrity ensure that data come from reliable sources and remain unaltered, preserving sensitive information from unauthorized access. Data privacy implements robust measures to safeguard against breaches, while location verification ensures data handling in an accurate, secure, and trustworthy manner. Our approach entails a comprehensive delineation, rigorous security analysis, and validation mechanism to fortify the protocol's legitimacy. A thorough assessment, encompassing formal and informal security analysis, validates its resilience against various attacks.