Stealthbits Introduces Automated Machine Learning to Data Access Governance at NetApp Insight

Stealthbits CTO, Jonathan Sander, recently returned from a road trip across the U.S. where he met with several customers. One of them remarked that finding sensitive data across his organization was like trying to find Waldo in the children’s book series, Where’s Waldo. The customer went on to say,

‘Even if we find it, we don’t have a foolproof way of keeping our sensitive information safe.’

He’s not the only one facing this dilemma. Organizations that have successfully implemented a least privileged model across their NetApp storage environments are vulnerable to insider threats. Attackers are like heat-seeking missiles that fly under the radar to find, access, and ultimately exfiltrate your most sensitive information. 

Consequently, organizations today need to adopt not only a Data Access Governance program that gives them visibility and control over their sensitive data, but also real-time Threat Detection to stop file system and account-based attacks—as well as threats like malware/ransomware.

At NetApp Insight this October 2-5 in Las Vegas, Stealthbits will show you how to safeguard your sensitive data by combining Machine Learning with state-of-the-art Data Access Governance. Through leveraging unsupervised Machine Learning to spot the most abnormal user behavior across millions of file accesses, you can zero-in on the handful of threats that warrant your attention. Generic User Behavior Analytics (UBA) products that rely on native logs for alerting can’t do that; they deliver undifferentiated warnings that you have to sift through to find what’s relevant.

The best part is these real-time threat analytics are part of your Data Access Governance solution so you can monitor unstructured data across your NetApp storage infrastructure from one easy-to-use dashboard.

Stop by our NetApp Insight Booth #403 to learn more and win a chance at a Wi-Fi Drone with HD Camera and Live Video.

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