- Abstract:
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This paper exploits publicly available aircraft meta data in conjunction with unfiltered air traffic communication gathered from a global collaborative sensor network to study the privacy impact of large-scale aircraft tracking on governments and public corporations. First, we use movement data of 542 verified aircraft used by 113 different governments to identify events and relationships in the real world. We develop a spatio-temporal clustering method which returns 47 public and 18 non-publ...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Accepted Manuscript
- Files:
-
-
(pdf, 3.0mb)
-
- Publisher copy:
- 10.1109/EuroSP.2018.00016
-
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- Publisher:
- IEEE Publisher's website
- Pages:
- 107-121
- Publication date:
- 2018-07-09
- Acceptance date:
- 2017-11-21
- DOI:
- Pubs id:
-
pubs:821729
- URN:
-
uri:3df6e2a7-f82a-4119-9326-6c658c559b8e
- UUID:
-
uuid:3df6e2a7-f82a-4119-9326-6c658c559b8e
- Local pid:
- pubs:821729
- ISBN:
- 978-1-5386-4228-3
- Copyright holder:
- Strohmeier et al.
- Copyright date:
- 2018
- Notes:
-
Copyright © 2018, Martin Strohmeier. Under license to IEEE. This is the accepted manuscript version of the paper. The final version is available online from IEEE at: https://doi.org/10.1109/EuroSP.2018.00016
Conference item
The real first class? Inferring confidential corporate mergers and government relations from air traffic communication
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