Abstract: Unfortunately no one is immune to security threats that are exponentially increasing in cost, impact, extent and complexity. Though there are traditional security approaches, they aren’t competent enough due to abundant information and lack of tools that don’t allow them to gain insight into the information to obtain knowledge about unknown threats. To resolve this problem as well as detect weak signals of threats that hide behind the noise of huge data in an organization, we have security intelligence platform that is a Big Data solution. This aim of this paper is to summarize why Big Data analytics is used for security intelligence, the ideal requirements of a platform designed for security purpose, how Big Data analytics is helpful compared to traditional approaches and the study of various platforms developed for security intelligence using Big Data analytics. Lastly we have a comparative study between the two most popular security intelligence platforms and then we discuss about how Big Data could be a dominant name in the field of security if it overcomes certain challenges.

Keywords: Anomaly, Beehive, Big Data, Big Data analytics, Intelligence driven security, IBM QRadar.