FINE: A fine-grained privacy-preserving location-based service framework for mobile devices

Abstract

In this paper, we propose a fine-grained privacy-preserving location-based service (LBS) framework, called FINE, for mobile devices. It adopts the data-as-a-service (DaaS) model, where the LBS provider publishes its data to a third party (e.g., cloud server) who executes users' LBS queries. The proposed FINE framework employs a ciphertext-policy anonymous attribute-based encryption technique to achieve fine-grained access control, location privacy, confidentiality of the LBS data and its access policy, and accurate LBS query result while without involving any trusted third party. Moreover, the proposed FINE framework also integrates the transformation key and proxy re-encryption to migrate most of computation-intensive tasks from the LBS provider and users to the cloud server. This property keeps mobile devices away from massive resource-consuming operations. Extensive analysis shows that our proposed FINE framework is secure and highly efficient for mobile devices in terms of computation and communication cost.