Space/time trade-offs in hash coding with allowable errors
Communications of the ACM
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
The Horus WLAN location determination system
Proceedings of the 3rd international conference on Mobile systems, applications, and services
Anonymous Usage of Location-Based Services Through Spatial and Temporal Cloaking
Proceedings of the 1st international conference on Mobile systems, applications and services
Private queries in location based services: anonymizers are not necessary
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Outsourcing Search Services on Private Spatial Data
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy
SSTD'07 Proceedings of the 10th international conference on Advances in spatial and temporal databases
Localization using radial basis function networks and signal trength fingerprints in WLAN
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Continuous All k-Nearest-Neighbor Querying in Smartphone Networks
MDM '12 Proceedings of the 2012 IEEE 13th International Conference on Mobile Data Management (mdm 2012)
The Airplace Indoor Positioning Platform for Android Smartphones
MDM '12 Proceedings of the 2012 IEEE 13th International Conference on Mobile Data Management (mdm 2012)
SmartP2P: A Multi-objective Framework for Finding Social Content in P2P Smartphone Networks
MDM '12 Proceedings of the 2012 IEEE 13th International Conference on Mobile Data Management (mdm 2012)
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The majority of smartphone localization systems use Assisted-GPS for fine-grained localization in outdoor spaces or WiFi-based RSS (Received Signal Strength) technologies for coarse-grain positioning in indoor and outdoor spaces. The former consumes precious energy from mobile devices, is strictly affected by the environment (e.g., cloudy day, forests, etc.) and does not work in indoor spaces. The latter collects RSS from WiFi beams within a user's vicinity and transfers an RSS vector to the server for localization, in which the position of the user is disclosed possibly violating users' privacy. In this paper, we present BloomMap, an innovative and efficient algorithm that conducts a localization process without unveiling the user's location to the localization service, minimizing the energy consumption of the mobile unit and also minimizing the network traffic by not transferring large positioning structures to the client (i.e., known as radiomap). Our framework is designed for planet-scale RSS localization scenarios, which are expected to emerge in the near-future. In particular, a user may localize itself using a subset of a vast data repository of RSS signals that is updated in real time by smartphone wardrivers. Our preliminary evaluation shows that our propositions can localize a device without unveiling its location in approximately 80% less time, energy and network resources than competitive approaches. We also describe our WiFi-based prototype system developed on the Android OS.