PrivateCheckIn: Trajectory Privacy-Preserving for Check-In Services in MSNS

Abstract

With the development of mobile devices and wireless networks,mobile social network services(MSNS) arise and develop fast.Check-in service as one of the most popular services in MSNS,has serious personal privacy leakage threats.In this paper,we propose a trajectory privacy-preserving method called PrivateCheckIn,which can protect trajectory privacy for pseudonym users in check-in services.At first,we buffer the check-in sequences of pseudonym users,and then we build prefix trees for buffered check-in sequences,prune and re-construct prefix trees to get the k-anonymized version.At last,we traverse the k-anonymized prefix tree to get k-anonymized check-in sequences,which can achieve a privacy guarantee of k-anonymity.We prove in this paper,PrivateCheckIn guarantees the number of lost check-in locations is minimized while satisfying users' privacy requirements.PrivateCheckIn also reduces the cost of finding trajectory k-anonymity set.At last,we run a set of comparative experiments with(k,δ)-anonymity on real-world datasets,the results show accuracy and effectiveness of PrivateCheckIn.