Conference Proceeding Article
Location-based services (LBS) are receiving increasing popularity as they provide convenience to mobile users with on-demand information. The use of these services, however, poses privacy issues as the user locations and queries are exposed to untrusted LBSs. Spatial cloaking techniques provide privacy in the form of k-anonymity; i.e., they guarantee that the (location of the) querying user u is indistinguishable from at least k-1 others, where k is a parameter specified by u at query time. To achieve this, they form a group of k users, including u, and forward their minimum bounding rectangle (termed anonymzing spatial region, ASR) to the LBS. The rationale behind sending an ASR instead of the distinct k locations is that exact user positions (querying or not) should not be disclosed to the LBS. This results in large ASRs with considerable dead-space, and leads to unnecessary performance degradation. Additionally, there is no guarantee regarding the amount of location information that is actually revealed to the LBS. In this paper, we introduce the concept of information leakage in spatial cloaking. We provide measures of this leakage, and show how we can trade it for better performance in a tunable manner. The proposed methodology directly applies to centralized and decentralized cloaking models, and is readily deployable on existing systems.
Dead-space, Existing systems, Information leakage, K-Anonymity, Location information, Location-Based Services, Minimum bounding rectangle, Mobile users, On-Demand, Performance degradation, Privacy issue, Query time, Spatial regions, User location
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
Advances in Spatial and Temporal Databases: 11th International Symposium, SSTD 2009 Aalborg, Denmark, July 8-10, 2009 Proceedings
City or Country
TAN, Kar Way; LIN, Yimin; and MOURATIDIS, Kyriakos.
Spatial Cloaking Revisited: Distinguishing Information Leakage from Anonymity. (2009). Advances in Spatial and Temporal Databases: 11th International Symposium, SSTD 2009 Aalborg, Denmark, July 8-10, 2009 Proceedings. 5644, 117-134. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/880
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