Enhancing C-V2X with Blockchain and Zero-Knowledge Proofs for Improved Privacy, and Trustworthiness

Abstract

This paper addresses the pivotal issue of privacy in traffic condition assessment within Cellular Vehicle-to-Everything (C-V2X) and Intelligent Transportation Systems, specifically targeting applications that do not have stringent low-latency requirements. Despite significant advancements in the field, existing approaches often fail to provide robust privacy protection without compromising network efficiency and data integrity. Our study is motivated by the pressing need to overcome these limitations through solutions that enhance network reliability, data privacy, and node reputation management. At the core of our approach is the implementation of Zero-Knowledge Proofs (ZKPs), which facilitate the secure verification of vehicular data while safeguarding individual privacy. We developed a method for aggregating ZKPs to improve data processing efficiency, thereby substantially reducing network load. Moreover, our application of machine learning techniques for node trustworthiness assessment further strengthens network integrity. The integration of blockchain technology in our framework addresses the traditional centralisation challenges in C-V2X, particularly in the areas of data storage, processing, and verification, thereby enhancing the network's security and resilience. Our framework bridges these gaps, resulting in a 90% reduction in computation and storage costs on-chain compared to a non-aggregated benchmark where each proof is submitted individually. Additionally, the node trustworthiness assessment reduces network delay by up to 31.7%.