论文标题
基于社会属性的轨迹隐私保护机制
Trajectory Privacy Protection Mechanism based on Social Attributes
论文作者
论文摘要
当前的轨迹隐私保护技术仅考虑轨迹数据的时间和空间属性，但忽略了社会属性。但是，社会属性与人类活动轨迹之间存在着内在的关系，这为轨迹隐私保护带来了新的挑战，从而使现有的轨迹隐私保护技术无法抵抗基于社会属性的轨迹隐私攻击。为此，本文首先研究了轨迹数据中的社会隐私攻击，基于“时空”特征的融合建立了社会隐私攻击模型，并揭示了轨迹数据中有关社会隐私泄漏的空间和时间特征的内部影响。 - 匿名算法和轨迹发布隐私保护提供理论支持。在此基础上，将社会属性集成到轨迹隐私保护技术中，设计基于“时空社会”三维移动模型的设计轨迹K-匿名算法，以及基于“时空社会 - 社会”的“多维“多维”相关性的“多维”轨迹数据。
The current trajectory privacy protection technology only considers the temporal and spatial attributes of trajectory data, but ignores the social attributes. However, there is an intrinsic relationship between social attributes and human activity trajectories, which brings new challenges to trajectory privacy protection, making existing trajectory privacy protection technologies unable to resist trajectory privacy attacks based on social attributes. To this end, this paper first studies the social privacy attack in the trajectory data, builds a social privacy attack model based on the fusion of "space-time" features, and reveals the internal impact of the spatial and temporal features in the trajectory data on social privacy leaks. -Anonymous algorithm and trajectory release privacy protection provide theoretical support. On this basis, integrate social attributes into trajectory privacy protection technology, design trajectory k-anonymity algorithm based on "space-time-social" three-dimensional mobile model, and construct trajectory data based on "space-time-social-semantic" multi-dimensional correlation Publish privacy-preserving models.
