期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2017
卷号：95
期号：24
页码：6719
出版社：Journal of Theoretical and Applied
摘要：In recent years, Location-Based Services (LBS) have become very popular, especially in the light of enhancements that are daily performed on both mobile devices and wireless networks. The popularity of LBS is derived from its valuable benefits, where they enable the users to search for nearest Points of Interest (POI), share ideas and comments, and enjoy playing games, making our life easier and more enjoyable. However, LBS have some risks associated with it. The privacy issue is considered one of the most important risks in this field since the users are forced to build their queries based on their real geographic locations. This paper studies the different privacy protection approaches through a survey, where a new classification is proposed based on the amount of collaboration between LBS users and LBS server. The protection goals (identity ID, Location Information LI, and Temporal Information TI) that any LBS user aims to protect are defined and measured. Based on the provided protection goals, the most advanced inference attacks (Location Homogeneity Attack LHA, Map Matching Attack MMA, Query Sampling Attack QSA, and Semantic Location Attack SLA) are analyzed and evaluated. As for challenges in LBS privacy protection field, an eight research questions and open problems are explored. In addition, we present some rules-based recommendations, which can help the LBS users to select the most optimal way to achieve a higher privacy protection level.
