College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Zhoushan Ocean Research Center, Zhoushan 316021, China.
Sensors (Basel). 2022 Jun 11;22(12):4423. doi: 10.3390/s22124423.
In the internet of vehicles (IoVs), vehicle users should provide location information continuously when they want to acquire continuous location-based services (LBS), which may disclose the vehicle trajectory privacy. To solve the vehicle trajectory privacy leakage problem in the continuous LBS, we propose a vehicle trajectory privacy preservation method based on caching and dummy locations, abbreviated as TPPCD, in IoVs. In the proposed method, when a vehicle user wants to acquire a continuous LBS, the dummy locations-based location privacy preservation method under road constraint is used. Moreover, the cache is deployed at the roadside unit (RSU) to reduce the information interaction between vehicle users covered by the RSU and the LBS server. Two cache update mechanisms, the active cache update mechanism based on data popularity and the passive cache update mechanism based on dummy locations, are designed to protect location privacy and improve the cache hit rate. The performance analysis and simulation results show that the proposed vehicle trajectory privacy preservation method can resist the long-term statistical attack (LSA) and location correlation attack (LCA) from inferring the vehicle trajectory at the LBS server and protect vehicle trajectory privacy effectively. In addition, the proposed cache update mechanisms achieve a high cache hit rate.
在车联网(IoV)中,车辆用户在需要获取连续的基于位置的服务(LBS)时应持续提供位置信息,这可能会泄露车辆轨迹隐私。为了解决连续 LBS 中的车辆轨迹隐私泄露问题,我们提出了一种基于缓存和虚拟位置的车辆轨迹隐私保护方法,简称 TPPCD,用于 IoV 中。在提出的方法中,当车辆用户想要获取连续的 LBS 时,使用基于道路约束的虚拟位置的位置隐私保护方法。此外,缓存部署在路边单元(RSU)中,以减少 RSU 覆盖的车辆用户与 LBS 服务器之间的信息交互。设计了两种缓存更新机制,即基于数据流行度的主动缓存更新机制和基于虚拟位置的被动缓存更新机制,以保护位置隐私并提高缓存命中率。性能分析和仿真结果表明,所提出的车辆轨迹隐私保护方法可以抵抗 LBS 服务器推断车辆轨迹的长期统计攻击(LSA)和位置相关攻击(LCA),有效保护车辆轨迹隐私。此外,所提出的缓存更新机制实现了高的缓存命中率。