Skip to Main content Skip to Navigation
Conference papers

The Fréchet/Manhattan Distance and the Trajectory Anonymisation Problem

Abstract : Mobile communication has grown quickly in the last two decades. Connections can be wirelessly established from almost any habitable place in the earth, leading to a plethora of connection-based tracking mechanisms, such as GPS, GSM, RFID, etc. Trajectories representing the movement of people are consequently being gathered and analysed in a daily basis. However, a trajectory may contain sensitive and private information, which raises the problem of whether spatio-temporal data can be published in a private manner.In this article, we introduce a novel distance measure for trajectories that captures both aspect of the microaggregation process, namely clustering and obfuscation. Based on this distance measure we propose a trajectory anonymisation heuristic method ensuring that each trajectory is indistinguishable from $$k-1$$ other trajectories. The proposed distance measure is loosely based on the Fréchet distance, yet it can be computed efficiently in quadratic time complexity. Empirical studies on synthetic trajectories show that our anonymisation approach improves previous work in terms of utility without sacrificing privacy.
Document type :
Conference papers
Complete list of metadata

Cited literature [27 references]  Display  Hide  Download

https://hal.inria.fr/hal-01633679
Contributor : Hal Ifip <>
Submitted on : Monday, November 13, 2017 - 11:46:28 AM
Last modification on : Friday, November 8, 2019 - 3:06:02 PM
Long-term archiving on: : Wednesday, February 14, 2018 - 2:38:11 PM

File

428203_1_En_2_Chapter.pdf
Files produced by the author(s)

Licence


Distributed under a Creative Commons Attribution 4.0 International License

Identifiers

Citation

Christof Torres, Rolando Trujillo-Rasua. The Fréchet/Manhattan Distance and the Trajectory Anonymisation Problem. 30th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec), Jul 2016, Trento, Italy. pp.19-34, ⟨10.1007/978-3-319-41483-6_2⟩. ⟨hal-01633679⟩

Share

Metrics

Record views

249

Files downloads

371