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.
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