A generalized quantification framework for evaluating user query privacy is proposed to address the overestimation of user's privacy protection level offered by query privacy protection mechanism in location-based services. The framework is to comprehensively take the various elements and relations that influence the query privacy of mobile users into account together and to formally define the mobile user
adversary
privacy protection mechanism and privacy metrics which reflect the user's privacy and service quality requirements. Moreover
the framework provides a systematic approach with integrating adversary's background knowledge available to and reasoning abilities in privacy quantification. The method can correctly evaluate the effectiveness of various query privacy protection mechanisms under the same conditions
and can help user to select appropriate privacy requirements to achieve a right tradeoff between privacy protection and service quality. The effectiveness and accuracy of the framework are verified through a set of experiments on datasets generated by network-based generator of moving objects proposed by Thomas Brinkhoff.
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