A Framework for Generating Network-Based Moving Objects
Geoinformatica
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
PRIVE: anonymous location-based queries in distributed mobile systems
Proceedings of the 16th international conference on World Wide Web
Preventing Location-Based Identity Inference in Anonymous Spatial Queries
IEEE Transactions on Knowledge and Data Engineering
Protecting Location Privacy with Personalized k-Anonymity: Architecture and Algorithms
IEEE Transactions on Mobile Computing
Supporting anonymous location queries in mobile environments with privacygrid
Proceedings of the 17th international conference on World Wide Web
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We propose a location-based query anonymization technique, LBS (k, T)-anonymization, that ensures anonymity of user's query in a specific time window against what we call known user attack. We distinguish between our technique and related work on k-anonymity for LBSs by showing that they target different privacy inference attacks. Also, we analyze the inconsistency of the existing predominant approach with the original definition of k-anonymity and its implications on the anonymization. Finally, we present an evaluation framework that assess the applicability and performance of the proposed technique using an evaluation framework.