Location Diversity: Enhanced Privacy Protection in Location Based Services

Abstract. Location-based Services are emerging as popular applications in pervasive computing. Spatial k-anonymity is used in Locationbased Services to protect privacy, by hiding the association of a specific query with a specific user. Unfortunately, this approach fails in many practical cases such as: (i) personalized services, where the user identity is required, or (ii) applications involving groups of users (e.g., employees of the same company); in this case, associating a query to any member of the group, violates privacy. In this paper, we introduce the concept of Location Diversity, which solves the above-mentioned problems. Location Diversity improves Spatial k-anonymity by ensuring that each query can be associated with at least different semantic locations (e.g., school, shop, hospital, etc). We present an attack model that maps each observed query to a linear equation involving semantic locations, and we show that a necessary condition to preserve privacy is the existenc...

• Type: Conference
• Year: 2009
• Where: LOCA
• Authors: Mingqiang Xue, Panos Kalnis, Hung Keng Pung
• Keywords: Information Management, LOCA 2009, Location Diversity, Semantic Locations, Spatial K-anonymity