Preventing location-based identity inference in anonymous spatial queries

Panos Kalnis*, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

546 Scopus citations


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 if-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.

Original languageEnglish (US)
Pages (from-to)1719-1733
Number of pages15
JournalIEEE Transactions on Knowledge and Data Engineering
Issue number12
StatePublished - Jan 1 2007
Externally publishedYes


  • Anonymity
  • Location-Based Services
  • Mobile systems
  • Privacy
  • Spatial databases

ASJC Scopus subject areas

  • Information Systems
  • Computer Science Applications
  • Computational Theory and Mathematics


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