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.
翻译:目前的轨迹隐私保护技术只考虑轨迹数据的时间和空间属性,而忽视了社会属性。然而,社会属性与人类活动轨迹之间存在内在关系,给轨迹隐私保护带来了新的挑战,使得现有的轨迹隐私保护技术无法抵制基于社会属性的轨迹隐私攻击。为此,本文件首先研究轨迹数据中的社会隐私攻击,根据“空间-时间”特征的融合,构建了社会隐私攻击模型,并揭示了社会隐私泄漏轨迹数据中空间和时间特征的内部影响。 - 匿名算法和轨迹释放隐私保护提供了理论支持。在此基础上,将社会属性纳入轨迹隐私保护技术,设计基于“空间-时间-社会-社会”三维移动模型的轨迹K-匿名算法,并基于“空间-时间-社会-世俗”多维相关数据构建轨迹数据。