A Scheme of Dynamic Location Privacy-Preserving with Blockchain in Intelligent Transportation System

Xuhan Zuo, Minghao Wang, Dayong Ye, Shui Yu

Abstract: In the promotion process of the Internet of Vehicles (IoV), location privacy issues arise when large-scale transmissions are applied. The current solutions for addressing location privacy issues in IoV are hindered by several pain points, including limited effectiveness, scalability challenges, and reliance on a single privacy mechanism. While a blockchain-based method for preserving location privacy has been proposed, there remains an academic concern regarding the suitability of such a scheme. In this paper, we propose a Dirichlet-based location privacy-preserving scheme for IoV, oriented towards vehicle density awareness and adjustable sensitivity by a certified organization. This scheme is applicable to intelligent transportation systems and addresses the limitations of current blockchain-based methods for preserving location privacy. Finally, we implement the proposed scheme in an industrial blockchain, evaluating its performance and conducting a theoretical analysis from security and privacy perspectives.