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Soft Computing

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01.10.2012 | Original Paper

Reidentification and k-anonymity: a model for disclosure risk in graphs

verfasst von: Klara Stokes, Vicenç Torra

Erschienen in: Soft Computing | Ausgabe 10/2012

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Abstract

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.

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Titel: Reidentification and k-anonymity: a model for disclosure risk in graphs
verfasst von: Klara Stokes
Vicenç Torra
Publikationsdatum: 01.10.2012
Verlag: Springer-Verlag
Erschienen in: Soft Computing / Ausgabe 10/2012
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-012-0850-4

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