Trajectory Anonymization: Balancing Usefulness about Position Information and Timestamp
Trajectory Anonymization: Balancing Usefulness about Position Information and Timestamp
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DOI：
10.1109/ntms.2019.8763833
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发表时间：
2019-06
期刊：
影响因子：
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通讯作者：
Tomoki Chiba;Y. Sei;Yasuyuki Tahara;Akihiko Ohsuga
中科院分区：
文献类型：
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作者：
Tomoki Chiba;Y. Sei;Yasuyuki Tahara;Akihiko Ohsuga
运动轨迹可以为所有领域提供有用的信息。然而，它们可能具有较高的隐私参数，与其他运营商共享轨迹数据而不进行匿名化会带来将移动轨迹与个人联系起来的风险。因此，有必要考虑将隐私保护应用于轨迹数据。匿名化指标，如k-匿名，通常被用于轨迹数据的匿名化。一些研究修改位置信息以实现匿名性。这种修改有时会导致数据集不准确。在这项研究中，为了减少位置的修改距离，我们提出了一种算法，允许在一定范围内获取位置信息时的时间不匹配。此外，我们定义的指标，代表扭曲的位置和时间信息。通过与已有方法的比较，验证了该方法的有效性。
Movement trajectories can provide useful information for all fields. However, they may have high privacy parameters, sharing trajectory data with other operators without anonymization carries the risk of linking movement trajectories to individuals. Therefore, it is necessary to consider applying privacy protection to trajectory data. Anonymization indicators, such as k—anonymity are generally adopted for anonymization of trajectory data. Some studies modify position information to achieve anonymity. This modification sometimes produces inaccuracies in data sets. In this study, to reduce the modification distance of the position, we propose an algorithm that allows the mismatch of time when the position information is acquired within a certain range. Further, we define indicators that represent distortions of position and time information. As a result of comparing the proposed method and the existing method, the usefulness of the proposed method is shown.