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The real first class? Inferring confidential corporate mergers and government relations from air traffic communication

Abstract:

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...

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Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1109/EuroSP.2018.00016

Authors


More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
ORCID:
0000-0002-1936-0933
More by this author
Institution:
University of Oxford
Division:
MPLS Division
Department:
Computer Science
Role:
Author
Publisher:
IEEE Publisher's website
Journal:
3rd IEEE European Symposium on Security and Privacy Journal website
Pages:
107-121
Host title:
2018 IEEE European Symposium on Security and Privacy (EuroS&P)
Publication date:
2018-07-09
Acceptance date:
2017-11-21
DOI:
Source identifiers:
821729
ISBN:
9781538642283
Pubs id:
pubs:821729
UUID:
uuid:3df6e2a7-f82a-4119-9326-6c658c559b8e
Local pid:
pubs:821729
Deposit date:
2018-01-28

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