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We consider Location-based Service (LBS) settings, where a LBS provider logsthe requests sent by mobile device users over a period of time and later wantsto publish/share these logs. Log sharing can be extremely valuable foradvertising, data mining research and network management, but it poses aserious threat to the privacy of LBS users. Sender anonymity solutions preventa malicious attacker from inferring the interests of LBS users by associatingthem with their service requests after gaining access to the anonymized logs.With the fast-increasing adoption of smartphones and the concern that historicuser trajectories are becoming more accessible, it becomes necessary for anysender anonymity solution to protect against attackers that aretrajectory-aware (i.e. have access to historic user trajectories) as well aspolicy-aware (i.e they know the log anonymization policy). We call suchattackers TP-aware.  This paper introduces a first privacy guarantee against TP-aware attackers,called TP-aware sender k-anonymity. It turns out that there are many possibleTP-aware anonymizations for the same LBS log, each with a different utility tothe consumer of the anonymized log. The problem of finding the optimal TP-awareanonymization is investigated. We show that trajectory-awareness renders theproblem computationally harder than the trajectory-unaware variants found inthe literature (NP-complete in the size of the log, versus PTIME). We describea PTIME l-approximation algorithm for trajectories of length l and empiricallyshow that it scales to large LBS logs (up to 2 million users).

Trajectory and Policy Aware Sender Anonymity in Location Based Services