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

Reidentification and \(k\)-anonymity: a model for disclosure risk in graphs
Authors: Klara Stokes; Vicenç Torra;

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

Abstract

In this article we provide a formal framework for reidentification in general. We define n-confusion as a concept for modelling 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.

Keywords

FOS: Computer and information sciences, Database tables, Computer Science - Cryptography and Security, \(n\)-confusion, \(k\)-anonymous graph, K-Anonymity, Formal framework, Disclosure risk, K-anonymization, Graph theory (including graph drawing) in computer science, Reidentification, FOS: Mathematics, Mathematics - Combinatorics, Combinatorics (math.CO), Cryptography and Security (cs.CR)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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40
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55
90
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