Paper 2025/1062

TrafficProof: Privacy-Preserving Reliable Traffic Information Sharing in Social Internet of Vehicles

Abstract

In the Social Internet of Vehicles (SIoV), effective data sharing is essential for applications including road safety, traffic management, and situational awareness. However, the decentralized and open nature of SIoV presents significant challenges in simultaneously ensuring data integrity, user privacy, and system accountability. This paper presents a protocol for secure and location-accurate traffic data sharing that fully preserves the anonymity and privacy of participating witnesses. The protocol leverages zero-knowledge proofs (ZKPs) to allow vehicles to broadcast redacted traffic information—such as images—tied to specific geographic locations, while withholding both the original content and the identity of the reporting vehicle. To ensure the authenticity of the redacted content and the legitimacy of the witness, an additional ZKP is used to privately validate both elements. Upon receiving a report, the verifying node checks the submitted proofs, aggregates validated inputs, and publishes the resulting metadata to both IPFS and a blockchain. This design ensures public verifiability, tamper resistance, and the reliability of the shared data, while maintaining strong privacy guarantees through cryptographic anonymity. To improve the efficiency of proof generation on resource-constrained devices, the protocol employs folding-based ZKP constructions. We conduct a formal security and soundness analysis of the protocol and implement a proof-of-concept, which is publicly available as open-source software. Experimental evaluations on commodity hardware demonstrate that the protocol is computationally efficient and introduces less than 1.5\% communication overhead relative to the size of the shared traffic data, indicating its suitability for real-world deployment.