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Application of security reference architecture to Big Data ecosystems in an industrial scenario
Author(s) -
Moreno Julio,
Gómez Javier,
Serrano Manuel A.,
B. Fernandez Eduardo,
FernándezMedina Eduardo
Publication year - 2020
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.2829
Subject(s) - big data , computer science , architecture , abstraction , ecosystem , data science , set (abstract data type) , environmental resource management , data mining , ecology , environmental science , geography , programming language , philosophy , archaeology , epistemology , biology
Summary Big Data environments are typically very complex ecosystems; this means that implementing them is complicated. One possible technique with which to address this complexity is the use of abstraction. Reference architecture (RA) can be useful for an improved understanding of the main components of Big Data. Herein, we propose a security RA that includes the management of security concerns and provides the main elements of a Big Data ecosystem. Application of this architecture to real‐world scenarios facilitates its refinement and improves its usefulness. In this article, we present a case study of a real‐world Big Data ecosystem implemented in a banking environment. This ecosystem was developed by everis, an NTT company with which we collaborated for this study. To conduct this validation case study, a map was established between the elements of the Big Data ecosystem implemented and our proposal. Consequently, a series of valuable lessons that can improve both our architecture and the security of the Big Data environment were obtained. These include recommendations for a set of best practices such as the use of security patterns.