Preserving User Location Privacy in Mobile Data Management Infrastructures

By Reynold Cheng, Yu Zhang, Elisa Bertino, Sunil Prabhakar. International Symposium on Privacy Enhancing Technologies, 2006

360 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Science Applications, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/f4e0eced09ae83207645a89ae760e40998bca2f9

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Citations in the corpus

SpaceTwist: Managing the Trade-Offs Among Location Privacy, Query Performance, and Query Accuracy in Mobile Services (2008, methodology): “With cloaking, the user location q is enlarged into a cloaked region Q' that is then used for querying the server [3]-[9], [12].”
Technical Privacy Metrics (2015, background): “4 Size of uncertainty region Location [27] 5.”
Private queries in location based services: anonymizers are not necessary (2008, background): “In [3], the CR is a closed region around the query point, which is independent of the number of users inside.”
Computing with Spatial Trajectories (2011, background): “The models for uncertain trajectories on road networks in terms of possible locations at a given time-instant have been considered in [5, 45, 83].”
Geo-indistinguishability: differential privacy for location-based systems (2012, background): “[10] proposes a location cloaking mechanism, and focuses on the evaluation of Location-based Range Queries.”
The new Casper: query processing for location services without compromising privacy (2006, background): “, [Bamba et al. 2008; Beresford and Stajano 2003; Chow et al. 2006; Chow and Mokbel 2007; Cheng et al. 2006; Duckham and Kulik 2005; Gedik and Liu 2008; Gruteser and Grunwald 2003; Ghinita et al. 2007a; 2007b; Gruteser and Liu 2004; Hashem and Kulik 2007; Hengartner and Steenkiste 2003; Hong and Lan”
Preventing Location-Based Identity Inference in Anonymous Spatial Queries (2007, background): “Probabilistic Cloaking [8] preserves the privacy of locations without applying spatial K -anonymity .”
Gearing resource-poor mobile devices with powerful clouds: architectures, challenges, and applications (2013, methodology): “Therefore, location cloaking should be adaptively tuned to balance the trade-off between privacy and result accuracy [15].”
Protecting Locations with Differential Privacy under Temporal Correlations (2014, background): “They generally use obfuscation meth-ods, such as spatial cloaking, cell merging, location precision reduction or dummy cells, to achieve anonymity based privacy or uncertainty based privacy (e.g., [4, 11, 20, 30]).”