Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/83147
Title: User-centric privacy-preserving collection and analysis of trajectory data
Author: Romero-Tris, Cristina  
Megias, David  
Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
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
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.
Keywords: trajectory data
Hilbert curve
anonymization group
frequent sequential pattern
DOI: 10.1007/978-3-319-29883-2_17
Type: info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/acceptedVersion
Issue Date: Feb-2016
Publication license: http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Appears in Collections:Articles

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