What if data security systems were so advanced that they didn’t just react to existing threats, they predicted them? What if these threats could be mitigated without human intervention using algorithm –based self-learning techniques? These are just some of the revolutionary benefits that big data systems can bring to enterprise data security.
Today’s globalized enterprise operates in an always-on environment involving multiple data flows of increasing complexity and greater distribution. This has resulted in a growing number of security threats as vast amounts of information are shared through the web, between devices and through transactions. Crucial to a comprehensive data security plan is the ability to keep pace with a variety of threats as and when they emerge. In light of this, big data analytics has emerged as a valuable solution for enterprise data security with techniques designed to sift through large volumes of data, correlate them and identify potential threats in real-time.
Enterprises have harnessed big data to create programs that mine and secure both historical and current information flows. Programs can be used to analyze unstructured data sources such as email and enterprise social networks, even securing data in motion. In addition crowdsourcing of threat intelligence is also gaining traction, as organizations begin to harness the collective intelligence of third-party users to keep up with emerging risks.
This is enabling enterprises to protect their data despite large volumes and numerous sources. Sensitive data from various sources can be identified and secured while potential threats can be separated for exploratory analytics by IT departments. Teams within organizations can be alerted in real-time and advised on how to respond.
These advanced methods of data security can be beneficial to organizations with expanding operations particularly because of their scalable nature. Financial providers can uncover frauds by correlating real-time and historical account data to spot abnormal user behavior. Big data analytics makes it possible to monitor single transactions across geographies and track card-swipes to ensure regulatory standards are met. Internet providers are matching HTTP transactions and DNS requests to identify communications associated with botnets. Enterprises are even employing linguistic analytics to spot suspicious behavior across communication channels.
Big data systems have helped evolve a fool-proof security system for enterprises by taking a predictive approach to security based on insights from vast amounts of enterprise data. These systems are capable of adapting to the changing threat landscape, providing a holistic view of the enterprise environment and driving actionable intelligence to protect against known and unknown threats. What are your thoughts on the potential of big data systems for enterprise security? Please leave your comments in the section below.