CSDL Home I ICDCS 2005 Proceedings. 25th IEEE International Conference on Distributed Computing Systems Workshops
June 6, 2005 to June 10, 2005
Buğra Gedik , Georgia Tech
Ling Liu , Georgia Tech
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDCS.2005.48
This paper describes a personalized k-anonymity model for protecting location privacy against various privacy threats through location information sharing. Our model has two unique features. First, we provide a unified privacy personalization framework to support location k-anonymity for a wide range of users with context-sensitive personalized privacy requirements. This framework enables each mobile node to specify the minimum level of anonymity it desires as well as the maximum temporal and spatial resolutions it is willing to tolerate when requesting for k-anonymity preserving location-based services (LBSs). Second, we devise an efficient message perturbation engine which runs by the location protection broker on a trusted server and performs location anonymization on mobile users? LBS request messages, such as identity removal and spatio-temporal cloaking of location information. We develop a suite of scalable and yet efficient spatio-temporal cloaking algorithms, called CliqueCloak algorithms, to provide high quality personalized location k-anonymity, aiming at avoiding or reducing known location privacy threats before forwarding requests to LBS provider(s). The effectiveness of our CliqueCloak algorithms is studied under various conditions using realistic location data synthetically generated using real road maps and traffic volume data.
Buğra Gedik, Ling Liu, "Location Privacy in Mobile Systems: A Personalized Anonymization Model", ICDCS, 2005, Proceedings. 25th IEEE International Conference on Distributed Computing Systems Workshops, Proceedings. 25th IEEE International Conference on Distributed Computing Systems Workshops 2005, pp. 620-629, doi:10.1109/ICDCS.2005.48