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Preventing location-based identity inference in anonymous spatial queries

Authors Kalnis, Panos
Ghinita, Gabriel
Mouratidis, Kyriakos
Papadias, Dimitris View this author's profile
Issue Date 2007
Source IEEE transactions on knowledge and data engineering , v. 19, (12), 2007, DEC, p. 1719-1733
Summary 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.
ISSN 1041-4347
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Language English
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