Using Big Data to Secure Big Data

I know you’ve probably been reading about RSA’s Big Data analytics play and if you’ve spent any time implementing and operating traditional security environments, you are just as excited about what predictive analytics can do to revolutionize security as I am.

As we look at the Big Data landscape, its volume, and its dynamic rate of change as well as its potential for exploitation given its maturity and overall threat surface, our single largest issue in protecting our emerging Big Data environments is scale.  Every node of Hadoop cluster has the potential to create massive amounts of application, network, and host operating system information.  When we combine this potential data deluge with the current limitations most security architectures already have around data capture and legitimate holistic event correlation the picture is bleak.

Now enter Big Data as a resolution to the scale issue.  A Big Data environment, mind you that is implemented with all the known problems solved (see Securing Big Data – The Scoop on Hadoop Part 1 and Part 2).

“We have to look to other security indicators and trusted security event data sources that will most probably lie outside of the traditional parameters.”

Lastly, we have to build in the function and logic to adjust the technology-based control points in accordance with initially reactive and eventually predictive events.  Without the later we are still providing too much of an opportunity for potentially malicious attacks.

As each of you compare and contrast how this view of the future security environment matches up against what you do today please bear in mind this is not an overnight transition.  We all have decades of legacy solutions that need to be evolved to fit into this new world.  Though daunting, it is a very exciting time to be part of a company that is leading the charge in transforming how we secure tomorrow’s data today.