But there's more to be gained by combining ZTM with big data. A promising approach is to apply behavioral analytics to data already resident in networks and so prevent a broad range of suspicious activities.
According to Gartner, big data analytics will play a crucial role in detecting cyberattacks. By 2016, more than 25% of global organizations will adopt big data analytics for at least one security and fraud-detection use case, up from the current 8%. Big data will change most of the product categories in the field of computer network security, including network monitoring, the authentication and authorization of users, identity management, fraud detection, and systems of governance, risk and compliance. Big data will also change the nature of the security controls, such as conventional firewalls, anti-malware and data loss prevention. In coming years, the tools of data analysis will evolve further to enable a number of advanced predictive capabilities and automated controls in real time.
Finally, the use of big data analytics in network security needs efficient data capture and analysis that can look broadly and historically across an infrastructure, sometimes trailing several months, to see when and how a breach occurred and what the consequences were. This process involves great volume, variety and velocity of data.
It's an open field for companies to introduce new products and services and harvest the profit.
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