Pervasive and Mobile Computing ( ) – Contents lists available at ScienceDirect Pervasive and Mobile Computing journal homepage: www.elsevier.com/locate/pmc Range-kNN queries with privacy protection in a mobile environment Zhou Shao a , David Taniar a , Kiki Maulana Adhinugraha a,b,∗ a Clayton School of Information Technology, Monash University, Victoria, Australia b School of Computing, Telkom University, Indonesia article info Article history: Available online xxxx Keywords: Range-kNN Voronoi Diagram Privacy Landmark Tree abstract With the help of location-based services (LBS), mobile users are able to access their actual locations, which can be used to search for information around them which they are inter- ested in. One typical thing is that mobile users are more likely to protect their personal information such as their actual locations. In order to protect the privacy of users’ personal information, we proposed Range-kNN queries, which uses the query range instead of one single query point. A Landmark Tree (LT), which indexes all the location information, is used to hide the actual user location in a specific radius. Through this LT, the query range, which covers the actual user location, is sent to the server for processing instead of the ac- tual user location. In the evaluation part, our algorithm is proved to be more precise than range queries, and the overall search performance is quite efficient. © 2015 Elsevier B.V. All rights reserved. 1. Introduction Mobile Computing [1], which enables mobile users to access the information they are interested in regardless of the user locations, has grown rapidly with the increasing number of mobile users. For mobile users, they are able to access the mobile information services [2–4], which provide various kinds of information in the mobile environment. Due to the large amount of mobile users, the privacy of users’ personal information becomes a big issue in the mobile environment. In the mobile environment, it is quite normal for mobile users to send their personal information to the server in order to access the mobile information service. During this process, the privacy of user information cannot be ensured as such information is likely to be accessed by the third party. Hence, mobile users are expecting more reliable mobile information services. Spatial queries [5,6] are often invoked by mobile users in the mobile environment in order to access mobile information services, such as searching for the nearest restaurants. Then for the spatial queries, which are based on the actual user lo- cation, is known as location-dependent queries [7]. For these kinds of spatial quires, they have to obtain the user location through LBS. kNN query [8–11] and range query [12–14] are two such queries which are based on the user location for query processing. kNN queries are invoked to find out k (k > 0) nearest neighbours based on the user location, while range queries are used to find all the neighbours for a given range which is a circular range regarding the user location as the centroid. However, for both of these two queries, the user location is necessary, which hazards the privacy of users’ personal informa- tion. Hence, we proposed Range-kNN queries [15], which uses the LT to hide mobile users’ locations, in order to protect the user information privacy for query processing. LT is the hierarchy structure of the landmarks, which can be used to replace ∗ Corresponding author at: Clayton School of Information Technology, Monash University, Victoria, Australia. E-mail addresses: zsha14@student.monash.edu (Z. Shao), david.taniar@monash.edu (D. Taniar), kiki.adhinugraha@monash.edu, kikimaulana@telkomuniversity.ac.id (K.M. Adhinugraha). http://dx.doi.org/10.1016/j.pmcj.2015.05.004 1574-1192/© 2015 Elsevier B.V. All rights reserved.