There are increasing risks of privacy disclosure when sharing the automotive location data in particular functions such as route navigation, driving monitoring and vehicle scheduling. These risks could lead to the attacks including user behavior recognition, sensitive location inference and trajectory reconstruction. In order to mitigate the data security risk caused by the automotive location sharing, this paper proposes a high-precision privacy protection mechanism based on format-preserving encryption (FPE) of geographical coordinates. The automotive coordinate data key mapping mechanism is designed to reduce to the accuracy loss of the geographical location data caused by the repeated encryption and decryption. The experimental results demonstrate that the average relative distance retention rate (RDR) reached 0.0844, and the number of hotspots in the critical area decreased by 98.9% after encryption. To evaluate the accuracy loss of the proposed encryption algorithm on automotive geographical location data, this paper presents the experimental analysis of decryption accuracy, and the result indicates that the decrypted coordinate data achieves a restoration accuracy of 100%. This work presents a high-precision privacy protection method for automotive location data, thereby providing an efficient data security solution for the sensitive data sharing in autonomous driving.

翻译：在路线导航、驾驶监控、车辆调度等特定功能中共享汽车位置数据时，隐私泄露风险日益增加。这些风险可能导致用户行为识别、敏感位置推断和轨迹重建等攻击。为缓解汽车位置共享引发的数据安全风险，本文提出一种基于地理坐标格式保留加密（FPE）的高精度隐私保护机制。通过设计汽车坐标数据密钥映射机制，降低了因重复加解密导致的地理位置数据精度损失。实验结果表明，加密后平均相对距离保持率（RDR）达到0.0844，关键区域热点数量减少98.9%。为评估所提加密算法对汽车地理位置数据的精度损失，本文进行了解密精度实验分析，结果显示解密后的坐标数据实现了100%的还原精度。本研究提出了一种高精度的汽车位置数据隐私保护方法，从而为自动驾驶中的敏感数据共享提供了高效的数据安全解决方案。