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Volume 16 Issue 1


k-Anonymity: From Theory to Applications

Sabrina De Capitani di Vimercati(a), Sara Foresti(a), Giovanni Livraga(a), Pierangela Samarati(a),(*)

Transactions on Data Privacy 16:1 (2023) 25 - 49

Abstract, PDF

(a) Computer Science Department, Università degli Studi di Milano, Italy.

e-mail:firstname.lastname @unimi.it; firstname.lastname @unimi.it; firstname.lastname @unimi.it; firstname.lastname @unimi.it


Abstract

k-Anonymity is a well-known privacy model originally designed to protect the identities of the individuals involved in the release of a data collection. It provides a privacy requirement and a metric able to capture the protection degree enjoyed by respondents (i.e., the individuals to whom released data refer). Since its proposal, k-anonymity has been heavily investigated, with works addressing extensions of its privacy requirement to capture specific privacy risks, approaches to efficiently enforce k-anonymity, and adaptations to application scenarios that go beyond the publication of a dataset. In this paper, we illustrate k-anonymity and its main extensions. We also discuss some of the main approaches proposed for the enforcement of the corresponding privacy requirements, and some advanced application scenarios.

* Corresponding author.


ISSN: 1888-5063; ISSN (Digital): 2013-1631; D.L.:B-11873-2008; Web Site: http://www.tdp.cat/
Contact: Transactions on Data Privacy; Vicenç Torra; Umeå University; 90187 Umeå (Sweden); e-mail:tdp@tdp.cat
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Vicenç Torra, Last modified: 23 : 18 January 31 2023.