Walk Alone and Be Fast: Trajectory Privacy-preserving in Complicated Environment
Zheng Huo, Ping He, Ruoyan Wei
Available Online August 2016.
- https://doi.org/10.2991/cset-16.2016.51How to use a DOI?
- Privacy-preserving, trajectory data publication, maximum speed attack
- 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.
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 BT - 2016 International Conference on Computer Science and Electronic Technology PB - Atlantis Press 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 -