Proceedings of the 2016 International Conference on Computer Science and Electronic Technology

Walk Alone and Be Fast: Trajectory Privacy-preserving in Complicated Environment

Authors
Zheng Huo, Ping He, Ruoyan Wei
Corresponding Author
Zheng Huo
Available Online August 2016.
DOI
https://doi.org/10.2991/cset-16.2016.51How to use a DOI?
Keywords
Privacy-preserving, trajectory data publication, maximum speed attack
Abstract
Trajectories are location samples ordered by sampling time, which is useful to multiple mobility-related applications. However, publication of these trajectories may cause serious personal privacy leakage. In this paper, we propose an approach called Walk Alone and Be Fast (WABF) to protect trajectory privacy against semantic location attack and maximum moving speed attack. WABF reduces the whole trajectories' exposure probability. At last, we conduct a set of comparative experimental studies on a real-world data set, the results show that WABF is effective and the information loss is much lower than k-anonymity methods.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Computer Science Research
Publication Date
August 2016
ISBN
978-94-6252-213-8
ISSN
2352-538X
DOI
https://doi.org/10.2991/cset-16.2016.51How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Zheng Huo
AU  - Ping He
AU  - Ruoyan Wei
PY  - 2016/08
DA  - 2016/08
TI  - Walk Alone and Be Fast: Trajectory Privacy-preserving in Complicated Environment
PB  - Atlantis Press
SP  - 219
EP  - 222
SN  - 2352-538X
UR  - https://doi.org/10.2991/cset-16.2016.51
DO  - https://doi.org/10.2991/cset-16.2016.51
ID  - Huo2016/08
ER  -