Proceedings of the 17th International Conference on World Wide Web 2008
DOI: 10.1145/1367497.1367531
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Supporting anonymous location queries in mobile environments with privacygrid

Abstract: This paper presents PrivacyGrid − a framework for supporting anonymous location-based queries in mobile information delivery systems. The PrivacyGrid framework offers three unique capabilities. First, it provides a location privacy protection preference profile model, called location P3P, which allows mobile users to explicitly define their preferred location privacy requirements in terms of both location hiding measures (e.g., location k-anonymity and location l-diversity) and location service quality measure… Show more

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Cited by 319 publications
(161 citation statements)
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“…Various privacy protection algorithms proposed for data privacy have been adopted for protecting location privacy of mobile users. The types of privacy protection algorithms include anonymization [1,5,8,10,13,20], data suppression [18], trajectory inference prevention [2,3,[14][15][16] and encryption [11]. While most of the existing schemes are aimed at preventing the adversary from distinguishing the location of a given user from that of other users, their perturbation techniques are mostly unidirectional and lack the ability to de-anonymize the perturbed information even when a user accessing the information has suitable credentials for obtaining finer information.…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Various privacy protection algorithms proposed for data privacy have been adopted for protecting location privacy of mobile users. The types of privacy protection algorithms include anonymization [1,5,8,10,13,20], data suppression [18], trajectory inference prevention [2,3,[14][15][16] and encryption [11]. While most of the existing schemes are aimed at preventing the adversary from distinguishing the location of a given user from that of other users, their perturbation techniques are mostly unidirectional and lack the ability to de-anonymize the perturbed information even when a user accessing the information has suitable credentials for obtaining finer information.…”
Section: Related Workmentioning
confidence: 99%
“…During the last several years, many location anonymization techniques [1,6,8,10,13,20] have been proposed. Most of them were developed as unidirectional cloaking techniques without considering the ability to de-anonymize the perturbed data.…”
Section: Introductionmentioning
confidence: 99%
“…presented a hierarchical partitioning method to improve the efficiency of location perturbation [14], however it was shown in [7] that this fails to provide location anonymity under non-uniform distribution of user locations. Selection of optimal subdivision spaces was investigated in [12,1]. Finally, in [7] a decentralized approach without an anonymizer was considered in order to realize a good load balancing property, however communication between users is required to calculate anonymized location information.…”
Section: Related Workmentioning
confidence: 99%
“…We can broadly classify the state of art research and development results into two categories. The first category is represented by location cloaking techniques [20,7,17,26,32]. Spatial location cloaking typically adds uncertainty to the location information exposed to the location query services by increasing the spatial resolution of a mobile user's locations while meeting location k-anonymity and/or location l-diversity [7].…”
Section: Introductionmentioning
confidence: 99%
“…The first category is represented by location cloaking techniques [20,7,17,26,32]. Spatial location cloaking typically adds uncertainty to the location information exposed to the location query services by increasing the spatial resolution of a mobile user's locations while meeting location k-anonymity and/or location l-diversity [7]. More specifically, the spatially cloaked region is constructed to ensure that at least k users (location k anonymity) are located in the same region, which contains l different static sensitive objects (locations).…”
Section: Introductionmentioning
confidence: 99%