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http://hdl.handle.net/10609/83147
Title: User-centric privacy-preserving collection and analysis of trajectory data
Author: Romero Tris, Cristina  
Megías Jiménez, David  
Others: Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Keywords: trajectory data
Hilbert curve
anonymization group
frequent sequential pattern
Issue Date: Feb-2016
Publisher: Lecture Notes in Computer Science
Citation: Romero-Tris, C. & Megías, D. (2016). User-centric Privacy-Preserving Collection and Analysis of Trajectory Data. Lecture Notes in Computer Science, 9481, 245-253. doi: 10.1007/978-3-319-29883-2_17
Published in: Lecture Notes in Computer Science, 9481
Project identifier: info:eu-repo/grantAgreement/TIN2011-27076-C03-02
info:eu-repo/grantAgreement/TIN2014-57364-C2-2-R
Also see: https://doi.org/10.1007/978-3-319-29883-2_17
Abstract: Due to the increasing use of location-aware devices such as smartphones, there is a large amount of available trajectory data whose improper use or publication can threaten users' privacy. Since trajectory information contains personal mobility data, it may reveal sensitive details like habits of behavior, religious beliefs, and sexual preferences. Current solutions focus on anonymizing data before its publication. Nevertheless, we argue that this approach gives the user no control about the information she shares. For this reason, we propose a novel approach that works inside users' mobile devices, where users can decide and configure the quantity and accuracy of shared data.
Language: English
URI: http://hdl.handle.net/10609/83147
ISBN: 9783319298832
ISSN: 0302-9743MIAR
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