Privacy / Security

Big Data Meets Threat Detection

In today’s world of threat detection, firewalls, proxies, and intrusion prevention systems, security professionals typically address known threats proactively by enforcing policies inline. They also act reactively to security threats by analyzing and correlating data with offline technologies like intrusion detection and security event management systems, which can feed policies defined in inline solutions.

I got to thinking about this the other day in the context of big data and emerging security analytics while I was talking with a colleague about the shift from monolithic computing to discrete distributed apps and computing endpoints. (Yes, we really talk about these sorts of things.) We noted that, as this happens, two things occur:

Companies are generating vast amounts of usable enterprise data.

Organizations are at a point in computing where they can actually use that data to make intelligent security decisions and be more efficient.

This poses great challenges and opportunities for enterprise IT, chief among them the lack of visibility and control over apps that consume enterprise data, and the incredible transience of data as it moves across the many apps that consume, manipulate, visualize, and make sense of it.

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