This is an excerpt from a post on the Q1 Labs Security Intelligence blog, contributed by Michael Applebaum, Director of Product & Segment Marketing at IBM Security Systems. You can follow him on Twitter at @ma08.
If you want to skate to where the puck is going in security today, it’s best to think big – as in Big Data. To detect stealthy breaches by advanced adversaries, you need to analyze a greater volume and variety of data, at a greater velocity – the so-called “3 V’s” of Big Data. Big Data analytics is as critical to security as to any other field, because it holds the promise of analyzing data sets too large to process in the past – in other words, solving previously unsolvable problems. In this way, it can help discover insights – such as security compromises or malicious behavior – that would have otherwise lay hidden.
The best way to obtain security analytics at Big Data scale is with a purpose-built security intelligence architecture that can scale to meet your needs, unpredictable as they might be. You want a solution that can expand as your business grows, as you analyze new types of security data, and as your security process maturity increases. One requiring minimal administration but offering maximum flexibility. In other words, a security intelligence cloud.
Just what is a security intelligence cloud? (No, it’s not a cloud-delivered security intelligence solution.)
Click here to read the rest of this blog post, and to learn about the building blocks of security intelligence.
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