Please use this identifier to cite or link to this item: http://hdl.handle.net/11422/9366
Type: Artigo
Title: Big data privacy context: literature effects on secure informational assets
Author(s)/Inventor(s): Rebello, Celina
Tavares, Elaine
Abstract: Indisponível.
Abstract: This article’s objective is the identification of research opportunities in the current big data privacy domain, evaluating literature effects on secure informational assets. Until now, no study has analyzed such relation. Its results can foster science, technologies and businesses. To achieve these objectives, a big data privacy Systematic Literature Review (SLR) is performed on the main scientific peer reviewed journals in Scopus database. Bibliometrics and text mining analysis complement the SLR. This study provides support to big data privacy researchers on: most and least researched themes, research novelty, most cited works and authors, themes evolution through time and many others. In addition, TOPSIS and VIKOR ranks were developed to evaluate literature effects versus informational assets indicators. Secure Internet Servers (SIS) was chosen as decision criteria. Results show that big data privacy literature is strongly focused on computational aspects. However, individuals, societies, organizations and governments face a technological change that has just started to be investigated, with growing concerns on law and regulation aspects. TOPSIS and VIKOR Ranks differed in several positions and the only consistent country between literature and SIS adoption is the United States. Countries in the lowest ranking positions represent future research opportunities.
Keywords: Big data
Multi-Criteria Decision Making (MCDM)
Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS)
Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR)
Bibliometrics
Subject CNPq: CNPQ::CIENCIAS SOCIAIS APLICADAS::ADMINISTRACAO
Department : Instituto COPPEAD de Administração
In: Transactions on Data Privacy
Volume: 11
Issue: 3
Issue Date: Dec-2018
Publisher country: Brasil
Language: por
Right access: Acesso Aberto
ISSN: 2013-1631
Appears in Collections:Ciências Sociais Aplicadas

Files in This Item:
File Description SizeFormat 
Big data privacy context-min.pdf274,1 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.