The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user identities. Nevertheless, the query contents may disclose the physical location of the user. In this paper, we present a framework for preventing location-based identity inference of users who issue spatial queries to location-based services. We propose transformations based on the well-established K-anonymity concept to compute exact answers for range and nearest neighbor search, without revealing the query source. Our methods optimize the entire process of anonymizing the requests and processing the transformed spatial queries. Extensive experimental studies suggest that the proposed techniques are applicable to real-life scenarios with numerous mobile users.
Mobile applications, Security and Privacy Protection, Spatial databases, location-based services
Databases and Information Systems | Numerical Analysis and Scientific Computing
Data Management and Analytics
IEEE Transactions on Knowledge and Data Engineering
KALNIS, Panos; GHINITA, Gabriel; MOURATIDIS, Kyriakos; and PAPADIAS, Dimitris.
Preventing Location-Based Identity Inference in Anonymous Spatial Queries. (2007). IEEE Transactions on Knowledge and Data Engineering. 19, (12), 1719-1733. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/205
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