Autor segons l'article: Salas J, Domingo-Ferrer J
Departament: Enginyeria Informàtica i Matemàtiques
Autor/s de la URV: Domingo Ferrer, Josep
Paraules clau: Privacy enhancing technologies Privacy by design statistical disclosure Differential privacy Control k-anonymity Big data privacy
Resum: © 2018, Springer International Publishing AG, part of Springer Nature. With the progress in the information and communication fields, new opportunities and technologies for statistical analysis, knowledge discovery, data mining, and many other research areas have emerged, together with new challenges for privacy and data protection. Nowadays several personal records are kept in computerized databases. Personal data is collected and kept in census databases, medical databases, employee databases, among others. There has always been an asymmetry between the benefits of computerized databases and the rights of individual data subjects. Some data protection principles can be derived from the legal framework. In this survey, we present some basic cryptographic and non-cryptographic techniques that may be used for enhancing privacy, we focus mainly on anonymization in databases and networks, discuss some differences and interactions among the well-known models of k-anonymity and differential privacy and finally present some challenges to privacy that come from big data analytics.
Àrees temàtiques: Mathematics, applied Computational theory and mathematics Computational mathematics Applied mathematics
ISSN: 16618289
Adreça de correu electrònic de l'autor: josep.domingo@urv.cat
Identificador de l'autor: 0000-0001-7213-4962
Pàgina final: 274
Data d'alta del registre: 2023-02-18
Volum de revista: 12
Versió de l'article dipositat: info:eu-repo/semantics/submittedVersion
Referència a l'article segons font original: Mathematics In Computer Science. 12 (3): 263-274
Referència de l'ítem segons les normes APA: Salas J, Domingo-Ferrer J (2018). Some basics on privacy techniques, anonymization and their big data challenges. Mathematics In Computer Science, 12(3), 263-274. DOI: 10.1007/s11786-018-0344-6
URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
Entitat: Universitat Rovira i Virgili
Any de publicació de la revista: 2018
Pàgina inicial: 263
Tipus de publicació: Journal Publications