Research On Social Relationship-based Location Privacy Preserving

With the development of the mobile Internet,applications based on location services have brought convenience to people's lives.The issue of privacy leakage caused by the release of location data and social relationship in social networks has attracted people's attention.It is of great significance to protect location data when publishing location data.Due to the assumption of independence between locations,the existing location privacy protection methods for offline location data publishing applied to real-world datasets will expose more location privacy information than expected.Friends in a social network(called social relationship)indicate that users are related to each other.Attackers use social relationship to attack the user's location,which will result in privacy leakage.Based on these considerations,a social relationship-based location privacy protection method(called RBLP)is given.When measuring user relevance,the existing location privacy protection methods don't take the social relationship into consideration.To solve this problem,user intimacy is defined,which uses social relationship and locations to measure the intimacy between users in the social network.Aiming at the problem of location privacy leakage caused by social relationship,a neighboring area selection mechanism and an intimacy-based location selection mechanism are proposed,which disturbs location data with differential privacy to weaken the location correlation between users.Compared with two different privacy protection methods on two datasets,which is called trajectory differential privacy and n-gram differential privacy,the experimental results show that: Under the same privacy budget,the location data generated by RBLP has better data utility than the other two methods.