Personalising privacy contraints in Generalization-based Anonymization Models

Personalising privacy contraints in Generalization-based Anonymization Models

Les bénéfices engendrés par les études statistiques sur les données personnelles des individus sont nombreux, que ce soit dans le médical, l'énergie ou la gestion du trafic urbain pour n'en citer que quelques-uns. Les initiatives publiques de smart-disclosure et d'ouverture des donnée...

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Bibliographic Details
Main Author:	Michel, Axel
Other Authors:	Bourges, INSA Centre Val de Loire
Language:	en
Published:	2019
Subjects:	Protection de la vie privée et des données Big Data Matériel sécurisé Data privacy and security Secure Hardware
Online Access:	http://www.theses.fr/2019ISAB0001/document

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