Path planning for privacy preserving in location based service

With the development of mobile networks and positioning technologies, location based service is becoming more and more popular, such as location-aware emergency response, advertisement, and car navigation system etc. However, while people enjoy more convenient life provided by location based services, their location privacy may leak. To tackle this problem, many researchers propose different ways to make users' privacy preserving and most of them focus on how to confuse users' true identities, or hide users' exact position while a user is in a cloaking square. The representative method is K-anonymity method which requires not less than k users in the same square when a location based service request occurs. In case there are not enough users in this cloaking square, the condition of the k-anonymity is not satisfied and location privacy would be leak. In this paper, we would tackle the problem of location privacy in a different way by predicating a safe path to users. Our objective is to provide more guarantee of privacy preserving for users under the K-anonymity criteria. We propose a path predicting algorithm from a user's current position to his/her destination. Every point on such path satisfies a location privacy policy under K-anonymity criteria. We also consider an upper threshold so as to balance privacy requirement and performance. Furthermore, the path would be dynamic adjusted according to users' movement and environment changes. Experiments are performed to verify our method and the experiment results show that this method is correct and efficient.