State-of-the-art Big Data Security Taxonomies

Today's businesses accumulate an astonishing amount of digital data, which can be leveraged to unlock new sources of economic value and provide fresh insights into business trends. The real challenge in this process is the design of computing, storage infrastructure and algorithms needed to handle this "Big Data". Hence, organizations are looking at different ways in which they can make use of Big Data in their business. There's no doubt that the creation of a Hadoop-powered Data Lake can provide a robust foundation for a new generation of analytics and intuitive results. At the same time, it is also very necessary to consider security before launching or expanding a Hadoop initiative. As we move towards a stage where Hadoop is considered for real-time production scenarios rather than just experimentation levels, a major chunk of production data is normally sensitive, or subject to many industry regulations and governance controls. This paper analyzes the current security challenges in big data implementations based on state-of-the-art big data security taxonomies.