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Reidentification and k-anonymity: a model for disclosure risk in graphs
Universitat Rovira i Virgili, Tarragona, Catalonia, Spain .
IIIA, Institut d’Investigació en Intel ligència Artificial CSIC, Bellaterra, Catalonia, Spain .
2012 (English)In: Soft Computing - A Fusion of Foundations, Methodologies and Applications, ISSN 1432-7643, E-ISSN 1433-7479, Vol. 16, no 10, 1657-1670 p.Article in journal (Refereed) Published
Abstract [en]

In this article we provide a formal framework for reidentification in general. We define n-confusion as a concept for modeling the anonymity of a database table and we prove that n-confusion is a generalization of k-anonymity. After a short survey on the different available definitions of k-anonymity for graphs we provide a new definition for k-anonymous graph, which we consider to be the correct definition. We provide a description of the k-anonymous graphs, both for the regular and the non-regular case. We also introduce the more flexible concept of (k, l)-anonymous graph. Our definition of (k, l)-anonymous graph is meant to replace a previous definition of (k, l)-anonymous graph, which we here prove to have severe weaknesses. Finally, we provide a set of algorithms for k-anonymization of graphs.

Place, publisher, year, edition, pages
Springer, 2012. Vol. 16, no 10, 1657-1670 p.
Keyword [en]
anonymity, data privacy, graph
National Category
Computer Science Information Systems Discrete Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-91463DOI: 10.1007/s00500-012-0850-4OAI: oai:DiVA.org:liu-91463DiVA: diva2:618006
Available from: 2013-04-25 Created: 2013-04-25 Last updated: 2017-12-06

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Stokes, Klara

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