CTPP: A Conditional Trajectory Privacy Preservation Scheme Using Blockchain in V2X

In Vehicle-to-Everything (V2X), the periodic broadcasting and reception of safety beacons by vehicles are pivotal for ensuring security. Nevertheless, the transmission of these messages in unencrypted formats over public channels presents substantial security risks. Adversaries with prior knowledge can potentially reconstruct the trajectories of targeted vehicles, thereby compromising sensitive information such as the behavioral patterns of drivers. To combat this issue, this article proposes a novel blockchain-based conditional trajectory privacy preservation (CTPP) scheme, which consists of two primary components: first, an attack-and-defense model is designed where a message blurring technique is utilized to resist the correlational background knowledge attack; second, the blockchain is introduced to enable the decentralized storage of beacon messages, thereby facilitating CTPP. Additionally, we develop two novel metrics, namely, the utility loss and the privacy loss, to evaluate the effectiveness of our CTPP. The former is quantified as the disparity between data sets pre and post the application of the privacy preservation mechanism. The latter is calculated as the proportion of the longest common subtrajectory (LCST) length to the original trajectory length. Extensive experimental results demonstrate that our CTPP significantly enhances trajectory privacy while incurring a moderate utility loss compared to the existing methods.

I. Introduction

Vehicle-to-Everything (V2X) is an emerging technology that seeks to improve safety, efficiency, and comfort for a vast amount of on-road services and applications via wireless communication techniques [1]. To expand the perception ranges and maintain a secure driving environment, each vehicle is configured to receive and analyze safety beacons sent periodically by its neighbors, which are termed as either the basic safety messages (BSMs) in SAE standards [2], [3] or the cooperative awareness messages (CAMs) in ETSI standards [4]. These messages play a critical role in augmenting drivers’ situational awareness, thereby facilitating preemptive actions to mitigate collision risks and optimize routing decisions. However, the transmission of these messages in unencrypted formats over inherently insecure channels raises substantial privacy concerns. Adversaries can exploit this vulnerability by extracting and correlating data such as location, speed, acceleration, and timestamps from these messages, enabling them to reconstruct vehicular trajectories and, consequently, infer sensitive personal information [5].