Research On User Location Privacy Protection In Crowd-sensing Networks

Crowd-Sensing Networks(CSN),as an important part of the Internet of Things,has been developing rapidly in recent years with the popularity of smart mobile devices and the progress of wireless network technology.However,most of the data collected by group intelligence sensing tasks contain user's sensitive information,especially user's location information,which leads to the leakage of user's location privacy.The risk of exposure.Existing location privacy protection methods for users in swarm intelligence perception networks require users to perform a large number of operations before sensing information,which increases the burden of users and reduces the enthusiasm of users to participate in perception tasks.This paper defines a new research background from the point of view of simplifying the operation of users participating in perception tasks and improving the enthusiasm of users participating in perception tasks,and uses differential privacy protection technology to protect users' location privacy.The main contents of this paper are as follows:(1)To protect user's location privacy when all users report the same accident point,DPALP(Differentially Private Accident Location Publish)algorithm based on differential privacy protection technology is adopted.The algorithm first locates the accident point,then uses Laplace mechanism to perturb the location coordinates of the accident point,and outputs the perturbed coordinates.Position coordinates of accident points.(2)Aiming at the user's location privacy protection problem when users report multiple accident occurrence locations,DPMALP(Differential Private Multiple Accident Locations Publish)algorithm based on differential privacy protection technology is adopted.First,a density-based clustering algorithm,is invoked to locate multiple accident occurrence locations and output multiple accidents.Then,Laplace mechanism is used to perturb the coordinates of the location points in the set of accident points,and finally the set of the location coordinates of the accident points after the perturbation is output.(3)The correctness and usability of DPALP algorithm and DPMALP algorithm used in this paper are verified by synthesizing data sets.