The paper entitled”Privacy Preserving Path Recommendation for Moving User on Location Based Service” was published in The 10th IEEE International Conference on Ubiquitous Intelligence and Computing.

Abstract—With the increasing adoption of location based services, privacy is becoming a major concern. To hide the identity and location of a request on location based service, most methods consider a set of users in a reasonable region so as to confuse their requests. When there are not enough users,the cloaking region needs expanding to a larger area or the response needs delay. Either way degrades the quality-of-service. In this paper, we tackle the privacy problem in a predication way by recommending a privacy-preserving path for a requester.We consider the popular navigation application, where users may continuously query different location based servers during their movements. Based on a set of metrics on privacy, distance and the quality of services that a LBS requester often desires, asecure path is computed for each request according to user’s preference, and can be dynamically adjusted when the situation is changed. A set of experiments are performed to verify our method and the relationship between parameters are discussed in details. We also discuss how to apply our method into practical applications.

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