PRIVAaaS : privacy approach for a distributed cloud-based data analytics platforms

PRIVAaaS : privacy approach for a distributed cloud-based data analytics platforms

Tania Basso, Regina Moraes, Nuno Antunes, Marco Vieira, Walter Santos, Meira Jr. Wagner

ARTIGO

Inglês

Agradecimentos: This work has been partially supported by the project EUBra-BIGSEA (www.eubra-bigsea.eu), funded by the Brazilian Ministry of Science, Technology and Innovation (Project 23614 - MCTI/RNP 3rd Coordinated Call) and by the European Commission under the Coope

Data privacy is a key challenge that is exacerbated by Big Data storage and analytics processing requirements. Big Data and Cloud Computing are related and allow the users to access data from any device, making data privacy essential as the data sets are

CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQ

FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE MINAS GERAIS - FAPEMIG

Fechado

PRIVAaaS : privacy approach for a distributed cloud-based data analytics platforms

Tania Basso, Regina Moraes, Nuno Antunes, Marco Vieira, Walter Santos, Meira Jr. Wagner


										

PRIVAaaS : privacy approach for a distributed cloud-based data analytics platforms

Tania Basso, Regina Moraes, Nuno Antunes, Marco Vieira, Walter Santos, Meira Jr. Wagner

    Fontes

    2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID)

    (July, 2017), p. 1108-1116