A Framework for Generating Network-Based Moving Objects
Geoinformatica
Location Privacy in Pervasive Computing
IEEE Pervasive Computing
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Location Based Services
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
The new Casper: query processing for location services without compromising privacy
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
On the anonymity of periodic location samples
SPC'05 Proceedings of the Second international conference on Security in Pervasive Computing
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Grid-based cloaking area creation scheme supporting continuous location-based services
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Preserving location privacy without exact locations in mobile services
Frontiers of Computer Science: Selected Publications from Chinese Universities
Balancing trajectory privacy and data utility using a personalized anonymization model
Journal of Network and Computer Applications
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Protection of users' privacy has been a central issue for location-based services (LBSs). In this paper, we classify two kinds of privacy protection requirements in LBS: location anonymity and identifier anonymity.While the location cloaking technique under the k-anonymity model can provide a good protection of users' privacy, it reduces the resolution of location information and, hence, may degrade the quality of service (QoS). To strike a balance between the location privacy and QoS, we present a quality-aware anonymity model for protecting location privacy while meeting user specified QoS requirements. In the model, a mobile user can specify the minimum anonymity level requirement upon location privacy as well as the maximum cloaking latency and the maximum cloaking region size requirements upon QoS. In accordance with the model, we develop an efficient directed-graph based cloaking algorithm to achieve both high-quality location anonymity and identifier anonymity. The performance objective is to maximize the cloaking success rate under the privacy and QoS constraints. Furthermore, we introduce an option of using dummy locations to achieve a 100% cloaking success rate at the cost of communication overhead. Experimental results show the effectiveness of our cloaking algorithm under various privacy and QoS requirements.