"ZK-V2XChain: Dataset for Zero-Knowledge Blockchain-Based Location Privacy in Vehicular Networks"

"This dataset supports the research presented in \u201cZK-V2XChain: A Zero-Knowledge Proof-Enabled Location Privacy Scheme for Sparse Vehicular Networks.\u201d It contains Floating Car Data (FCD) generated using Eclipse SUMO (v1.22.0) for a case study in Tudun Wada area, Kano State, Nigeria. The simulation includes mobility traces, pseudonym exchange logs, entropy and anonymity metrics, blockchain-based identity token authentication results, and ablation studies comparing our scheme against six baseline methods. Key files include SUMO configuration files, MATLAB scripts, vehicle request logs, retry distributions, communication overhead comparisons, and entropy plots. This dataset enables reproducibility of privacy-performance trade-offs in vehicular networks and supports future benchmarking of secure V2X communication protocols in African urban environments."

本数据集为《ZK-V2XChain：面向稀疏车联网的零知识证明（Zero-Knowledge Proof）赋能位置隐私方案》（ZK-V2XChain: A Zero-Knowledge Proof-Enabled Location Privacy Scheme for Sparse Vehicular Networks）相关研究提供支撑。数据集包含基于Eclipse SUMO（v1.22.0）生成的浮动车数据（Floating Car Data, FCD），用于尼日利亚卡诺州图敦瓦达区域的案例研究。本次仿真涵盖移动轨迹、假名交换日志、熵与匿名性指标、基于区块链的身份Token认证结果，以及将本方案与六种基线方法开展对比的消融实验。核心文件包括SUMO配置文件、MATLAB脚本、车辆请求日志、重试分布、通信开销对比结果与熵值绘图文件。本数据集可实现车联网场景下隐私与性能权衡相关研究的复现，并为非洲城市环境中安全V2X（Vehicle to Everything）通信协议的后续基准测试提供支撑。