APS: Attribute-aware privacy-preserving scheme in location-based services

As one of the most significant factors for privacy protection, side information has been considered in designing privacy-preserving schemes in Location-Based Services (LBSs) over recent years. However, most existing schemes consider this concept through a straightforward way, such as query probability. In this paper, we consider the basic attribute associating with each location and design an Attribute-aware Privacy-preserving Scheme (APS) to enhance mobile user's location privacy. Specifically, we first extract basic attributes from the local map, and specialize the Attribute-Aware Side Information (AASI). Then we build an attribute-based hierarchical tree (A-tree), which classifies locations into different categories in term of each location's attribute. Based on such information, we design APS, which consists of two algorithms, Voronoi Dividing Algorithm (VDA) and Dummy Determining Algorithm (DDA). In VDA, we divide the local map into different Voronoi polygons based on the properties of Voronoi Diagram, which guarantees the selected locations are dispersed. In DDA, we utilize the Four Color Map Theorem to color these Voronoi polygons, which helps mobile users to choose the dummy locations as far as possible. Therefore, our APS provides an optimal dummy set to protect mobile user's location privacy and query privacy. Finally, thorough analysis and evaluation results illustrate the effectiveness and efficiency of our proposed scheme. (C) 2019 Published by Elsevier Inc.