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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: | |
URI: | http://hdl.handle.net/10609/83147 |
ISBN: | 9783319298832 |
ISSN: | 0302-9743MIAR |
Appears in Collections: | Articles |
Files in This Item:
File | Description | Size | Format | |
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postprint_UsercentricRomeroMegias.pdf | Postprint | 211,93 kB | Adobe PDF | ![]() View/Open |
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