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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.
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)
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)
| 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). | 40 | |
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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