Towards a Security Reference Architecture for Big Data

Companies are aware of Big Data importance as data are essential to conduct their daily activities, but new problems arise with new technologies, as it is the case of Big Data; these problems are related not only to the 3Vs of Big Data, but also to privacy and security. Security is crucial in Big Data systems, but unfortunately, security problems occur due to the fact that Big Data was not initially conceived as a secure environment. Furthermore, this task is difficult due to the heterogeneous configurations that a Big Data system can have. One way to solve this problem is by having a global perspective, and in this way, a Reference Architecture (RA) is a high-level abstraction of a system that can be useful in the implementation of complex systems. Several initiatives have been made for obtaining a RA for Big Data like those from IBM, ORACLE, NIST or ISO, but none of them have their main focus on security. It is widely accepted that adding elements to address threats and facilitate the definition of security requirements to RA is a good starting point for solving these kind of threats and, in this way, converting RAs into Security Reference Architectures (SRAs). In the current paper, a SRA for Big Data is defined using UML models trying to ease secure Big Data implementations; allowing to apply security patterns in order to secure final Big