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An Enhanced Method of Trajectory Privacy Preservation Through Trajectory Reconstruction

机译：一种通过轨迹重构保护轨迹隐私的增强方法

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摘要

Trajectory data of mobile users contain plenty of sensitive spatial and temporal information, and can support many applications through data analysing and mining. However, re-identification attack and inference attack on such data may cause serious personal privacy leakage. Existing privacy preserving techniques cannot protect trajectory privacy well or largely scarify data utility. In view of these issues, in this paper we propose an enhanced trajectory privacy preserving method which can protect the trajectory privacy preferably while maintaining a high utility of the trajectory in data publishing. A mechanism is proposed to protect the privacy through replacing stop points in the trajectory and an effective trajectory reconstruction algorithm is introduced to avoid the mutations of trajectory, and also deal with the possible presence of obstacles around trajectories. The performance of our proposal is comprehensively evaluated on a real trajectory dataset. The results show that our method achieves a high privacy level and improves the utility of trajectory data greatly, compared with the state-of-the-art method.
机译：移动用户的轨迹数据包含大量敏感的时空信息，并且可以通过数据分析和挖掘来支持许多应用程序。但是，对此类数据的重新识别攻击和推断攻击可能会导致严重的个人隐私泄露。现有的隐私保护技术不能很好地保护轨迹的隐私，或者大大削弱了数据的实用性。鉴于这些问题，本文提出了一种改进的轨迹隐私保护方法，该方法可以在保持轨迹在数据发布中的高度实用性的同时，更好地保护轨迹隐私。提出了一种通过替换轨迹中的停靠点来保护隐私的机制，并提出了一种有效的轨迹重构算法来避免轨迹发生突变，并解决轨迹周围可能存在的障碍。我们的建议的性能是在真实的轨迹数据集上进行综合评估的。结果表明，与最新方法相比，我们的方法具有较高的隐私级别，并大大提高了轨迹数据的实用性。

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