Secure Data Provenance in Internet of Vehicles with Data Plausibility for Security and Trust

The evolution of the Internet of Vehicles (IoVs) presents many opportunities for intelligent transport systems; however, it brings significant security challenges that threaten the security and reliability of the data. Security, reliability, and trustworthiness are the essential critical requirements for the IoVs to ensure secure and efficient decision-making processes in an accurate, secure, and trustworthy manner. Traditional research paradigms have predominantly focused on data integrity, overlooking the essential need for data to be realistic, consistent, trustworthy, and reliable. Addressing this gap, our paper introduces a decentralized secure data provenance (SDP) protocol for the dynamic and distributed nature of IoVs to ensure verifiable security properties regarding data plausibility, source identity, data privacy, location authenticity, and data integrity, properties that are fundamental for achieving SDP. Our protocol integrates Verifiable Credentials (VCs) with distributed ledger technology (DLT), Road-Side Unit (RSU) infrastructure, cryptographic techniques, and plausibility checks to ensure secure, traceable, and tamper-evident data lineage. This comprehensive approach enables the timely identification and mitigation of potential security breaches, such as impersonation, data tampering, and privacy violations which are crucial for maintaining SDP and ensuring data credibility through anomaly detection and plausibility checks. Through detailed security analysis and validation, our methodology demonstrates improved resilience against common threats, ensuring that only credible and verifiable data inform its decision-making processes.