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Logical foundations of privacy-preserving publishing of linked data

Abstract:

The widespread adoption of Linked Data has been driven by the increasing demand for information exchange between organisations, as well as by data publishing regulations in domains such as health care and governance. In this setting, sensitive information is at risk of disclosure since published data can be linked with arbitrary external data sources

In this paper we lay the foundations of privacy-preserving data publishing (PPDP) in the context of Linked Data. We consider anonymisa...

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Publication status:
Accepted
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Role:
Author
Royal Society More from this funder
Engineering and Physical Sciences Research Council More from this funder
Publisher:
Association for the Advancement of Artificial Intelligence Publisher's website
Host title:
Proceedings of the 30th AAAI Conference on Artificial Intelligence
Publication date:
2015-01-01
EISSN:
2374-3468
ISSN:
2159-5399
Source identifiers:
577321
Pubs id:
pubs:577321
UUID:
uuid:51203886-45e9-430c-b95c-c0ea6d238656
Local pid:
pubs:577321
Deposit date:
2015-12-01

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