k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Location Privacy in Mobile Systems: A Personalized Anonymization Model
ICDCS '05 Proceedings of the 25th IEEE International Conference on Distributed Computing Systems
Vehicular Mobility Simulation for VANETs
ANSS '07 Proceedings of the 40th Annual Simulation Symposium
Preserving privacy in gps traces via uncertainty-aware path cloaking
Proceedings of the 14th ACM conference on Computer and communications security
Micro-Blog: sharing and querying content through mobile phones and social participation
Proceedings of the 6th 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
Place-Its: a study of location-based reminders on mobile phones
UbiComp'05 Proceedings of the 7th international conference on Ubiquitous Computing
Virtual individual servers as privacy-preserving proxies for mobile devices
Proceedings of the 1st ACM workshop on Networking, systems, and applications for mobile handhelds
Hiding stars with fireworks: location privacy through camouflage
Proceedings of the 15th annual international conference on Mobile computing and networking
Privately querying location-based services with SybilQuery
Proceedings of the 11th international conference on Ubiquitous computing
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Users face privacy risks when providing personal location data to untrusted location based services (LBSs). Many existing attempts to anonymize users have relied on suppressing information about users' locations. This suppression results in reduced functionality, including degraded spatial accuracy or the loss of realtime location updates. We propose anonymizing a user by camouflaging their current location with various predicted paths. This is akin to increasing the noise floor around the user. We believe this different approach provides many advantages. By allowing the user to keep all desired functionality while still protecting the user's privacy, we enable use of a broader class of LBSs. To demonstrate our proposal, we develop CacheCloak, a system that enables realtime anonymization of continuous location updates without any loss of accuracy. Data from a GIS-based traffic simulation in an urban environment shows that CacheCloak can anonymize users rapidly.