The trade-off among individual privacy,data utility and data feature of service has been a great concern when designing and evaluating privacy preserv-ing schemes in trajectories publishing.The trajectories data is spatial and temporal correlated strongly.So,Privacy-preserving over them should take the human be-haviors and their status into account.In this paper,we develop a novel method to investigate and analyze users' behaviors as well as the crowd density after ab-stracting users' ROIs.Finally,we evaluate the privacy stress via a well-designed indictor combing the trajectories visualization and analyzation.Experiments show that the method is capable of effectively finding both crowd living patterns and distribution,and the proposed indictor can quantize the mobility data utility pre-cisely in grid.