Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/70146
Title: Preserving user location privacy in mobile data management infrastructures
Authors: Cheng, R
Zhang, Y
Bertino, E
Prabhakar, S
Issue Date: 2006
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2006, v. 4258, p. 393-412 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Location-based services, such as finding the nearest gas station, require users to supply their location information. However, a user’s location can be tracked without her consent or knowledge. Lowering the spatial and temporal resolution of location data sent to the server has been proposed as a solution. Although this technique is effective in protecting privacy, it may be overkill and the quality of desired services can be severely affected. In this paper, we suggest a framework where uncertainty can be controlled to provide high quality and privacy-preserving services, and investigate how such a framework can be realized in the GPS and cellular network systems. Based on this framework, we suggest a data model to augment uncertainty to location data, and propose imprecise queries that hide the location of the query issuer and yields probabilistic results. We investigate the evaluation and quality aspects for a range query. We also provide novel methods to protect our solutions against trajectory-tracing. Experiments are conducted to examine the effectiveness of our approaches.
Description: 6th International Workshop on Privacy Enhancing Technologies, PET 2006, Cambridge, UK, June 28-30, 2006
URI: http://hdl.handle.net/10397/70146
ISBN: 978-3-540-68790-0
978-3-540-68793-1
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/11957454_23
Appears in Collections:Conference Paper

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