Murdoch University Research Repository

Welcome to the Murdoch University Research Repository

The Murdoch University Research Repository is an open access digital collection of research
created by Murdoch University staff, researchers and postgraduate students.

Learn more

Vehicloak: A blockchain-enabled privacy-preserving payment scheme for location-based vehicular services

Guo, Y., Wan, Z., Cui, H.ORCID: 0000-0002-5820-2233, Cheng, X. and Dressler, F. (2022) Vehicloak: A blockchain-enabled privacy-preserving payment scheme for location-based vehicular services. IEEE Transactions on Mobile Computing . Early Access.

Link to Published Version:
*Subscription may be required


The Internet of Vehicles (IoV) technology enables vehicles to communicate with each other, with pedestrians and with roadside infrastructures, to realize more efficient, safer and more environmentally friendly transportation. IoV also promises rich location-based services for vehicles, such as parking and toll highway. However, preserving privacy for location-based service payments emerges as a critical and challenging problem in IoV. Existing schemes rely on centralized banks for payment processing, resulting in location privacy leakage to centralized entities. In this paper, we propose a decentralized privacy-preserving payment scheme named Vehicloak for IoV based on the blockchain technology. The biggest challenge is to provide location privacy for vehicles while guaranteeing correct service payments using the transparent blockchain. To tackle this challenge, we introduce a new cryptographic technique called zk-GSigproof that integrates zero-knowledge proof with group signature. Vehicloak implements this technique in a smart contract to process payment, which verifies zero-knowledge proof and group signature without leaking location information. It is not limited to IoV and can be applied in many payment scenarios. To evaluate the performance of our scheme, we implement Vehicloak on a private blockchain of 100 nodes on Aliyun, and conduct a test with up to 4,000 transactions. The experimental results prove the feasibility of Vehicloak.

Item Type: Journal Article
Murdoch Affiliation(s): Information Technology, Mathematics and Statistics
Publisher: IEEE
Copyright: © Copyright 2022 IEEE
Item Control Page Item Control Page