Location-based services (LBSs) in vehicular ad hoc networks (VANETs) offer users numerous conveniences. However, the extensive use of LBSs raises concerns about the privacy of users' trajectories, as adversaries can exploit temporal correlations between different locations to extract personal information. Additionally, users have varying privacy requirements depending on the time and location. To address these issues, this paper proposes a personalized trajectory privacy protection mechanism (PTPPM). This mechanism first uses the temporal correlation between trajectory locations to determine the possible location set for each time instant. We identify a protection location set (PLS) for each location by employing the Hilbert curve-based minimum distance search algorithm. This approach incorporates the complementary features of geo-indistinguishability and distortion privacy. We put forth a novel Permute-and-Flip mechanism for location perturbation, which maps its initial application in data publishing privacy protection to a location perturbation mechanism. This mechanism generates fake locations with smaller perturbation distances while improving the balance between privacy and quality of service (QoS). Simulation results show that our mechanism outperforms the benchmark by providing enhanced privacy protection while meeting user's QoS requirements.

翻译：在车载自组织网络（VANETs）中，基于位置的服务（LBSs）为用户带来了诸多便利。然而，LBSs的广泛应用引发了对用户轨迹隐私的担忧，因为攻击者可利用不同位置间的时间相关性提取个人信息。此外，用户在不同时间和地点具有差异化的隐私需求。针对这些问题，本文提出了一种个性化轨迹隐私保护机制（PTPPM）。该机制首先利用轨迹位置的时间相关性确定每个时刻的可能位置集。我们通过基于希尔伯特曲线的最小距离搜索算法为每个位置确定保护位置集（PLS），该方法融合了地理不可区分性与失真隐私的互补特性。我们提出了一种新颖的置换-翻转机制用于位置扰动，将其在数据发布隐私保护中的初始应用映射为位置扰动机制。该机制在生成扰动距离更小的虚假位置的同时，改善了隐私与服务质量（QoS）之间的平衡。仿真结果表明，我们的机制在满足用户QoS需求的前提下，相比基准方法提供了更强的隐私保护。