Bhuvan Bamba, Ling Liu,
PRIVACYGRID: Supporting Anonymous Location Queries in Mobile Environments
We present PRIVACYGRID − a framework for supporting anonymous location-based queries in mobile information delivery systems. The PRIVACYGRID framework offers three unique capabilities. First, we provide a location privacy 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 measures (e.g., maximum spatial resolution and maximum temporal resolution). Second, we develop three fast and effective location cloaking algorithms for providing location k-anonymity and location l-diversity
in a mobile environment. The Quad Grid cloaking algorithm is fast but has lower anonymization success rate. The dynamic bottom-up or top-down grid cloaking algorithms provide much higher anonymization success rate and yet are efficient
in terms of both time complexity and maintenance cost.
Finally, we discuss a hybrid approach that combines the top-down and bottom-up search of location cloaking regions to further lower the average anonymization time. In addition, we argue for incorporating temporal cloaking into the location cloaking process to further increase the success rate of location anonymization. We also discuss the PRIVACYGRID mechanisms for anonymous support of range queries. Our experimental evaluation shows that the PRIVACYGRID approach can provide optimal location anonymity as defined by per user location P3P without introducing significant performance penalties.