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Techniques d'anonymisation tabulaire : concepts et mise en oeuvre

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arxiv 2001.02650 v1 pith:GLCSYKQR submitted 2020-01-08 cs.CR cs.CYcs.DB

classification cs.CRcs.CYcs.DB
keywords documentanonymisationanonymizationconceptstechniquesdonnknowledgeoeuvre
verification ladder T0 review T1 audit T2 compute T3 formal
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In this document, we present a state of the art of anonymization techniques for classical tabular datasets. This article is geared towards a general public having some knowledge of mathematics and computer science, but with no need for specific knowledge in anonymization. The objective of this document it to explain anonymization concepts in order to be able to sanitize a dataset and compute reindentification risk. The document contains a large number of examples to help understand the calculations. ----- Dans ce document, nous pr\'esentons l'\'etat de l'art des techniques d'anonymisation pour des bases de donn\'ees classiques (i.e. des tables), \`a destination d'un public technique ayant une formation universitaire de base en math\'ematiques et informatique, mais non sp\'ecialiste. L'objectif de ce document est d'expliquer les concepts permettant de r\'ealiser une anonymisation de donn\'ees tabulaires, et de calculer les risques de r\'eidentification. Le document est largement compos\'e d'exemples permettant au lecteur de comprendre comment mettre en oeuvre les calculs.

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Cited by 1 Pith paper

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  1. Anonymity-washing

    cs.CR 2025-05 conditional novelty 4.0 of 10

    A review paper defines 'anonymity-washing' and argues that vague regulations, outdated techniques, and poor training let organizations mislabel personal data as anonymous.

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