  Collection of user's location and trajectory information that contains rich
personal privacy in mobile social networks has become easier for attackers.
Network traffic control is an important network system which can solve some
security and privacy problems. In this paper, we consider a network traffic
control system as a trusted third party and use differential privacy for
protecting more personal trajectory data. We studied the influence of the high
dimensionality and sparsity of trajectory data sets based on the availability
of the published results. Based on similarity point aggregation reconstruction
ideas and a prefix tree model, we proposed a hybrid publishing method of
differential privacy spatiotemporal trajectory data sets APTB.
