PPTM-IoV: a privacy-preserving trust management framework for the Internet of Vehicles (IoV)

Abstract

The Internet of Vehicles (IoV) enables seamless Vehicle-to-Everything (V2X) communication among connected vehicles, infrastructure, and cloud services, supporting Intelligent Transportation Systems (ITS) through real-time information exchange. However, the dynamic and decentralized nature of IoV environments introduces significant challenges related to trust management, privacy preservation, and secure communication. To address these challenges, in this paper, we propose PPTM-IoV, a privacy-preserving trust management framework that enables vehicles to establish trust without revealing their private data. The framework first introduces a privacy-preserving identity and credential management scheme that uses pseudonymous identities and verifiable credentials, combined with a non-interactive zero-knowledge proof (ZKP) mechanism based on established cryptographic techniques. Next, a dynamic trust evaluation mechanism is designed by combining direct observations and weighted indirect recommendations. The trust model is further strengthened with adaptive updating based on significant behavioral changes and supported by analytical properties. To protect sensitive trust information during outsourced computation, the framework employs Paillier-based homomorphic encryption, enabling secure trust aggregation in the encrypted domain. A privacy-preserving trust processing workflow is achieved by integrating homomorphic computation with trusted-authority-assisted proxy re-encryption. Furthermore, a proxy re-encryption mechanism supports authorized trust verification between vehicles without exposing trust scores to unauthorized entities. Finally, a secure and trust-aware communication protocol incorporates bidirectional trust verification, threshold-based decision-making, and encrypted as well as digitally signed message exchange to ensure confidentiality, integrity, and mutual trust enforcement. The proposed framework is implemented using SUMO and NS-3 simulators. Experimental results demonstrate that PPTM-IoV achieves superior performance compared to the best-performing benchmark schemes, reducing average latency by 4.80%, while improving PDR by 1.43%, throughput by 4.09%, and trust accuracy by 1.47%.