  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.
