Revealing cyber threats with AI and Exabeam
Using advanced machine learning to address cyber security problems from a business’s standpoint.
Show Notes for Series 03 Episode 03
This podcast is produced in association with Exabeam.
A vital part of any organization’s cybersecurity arsenal is a SIEM system (security information and event management). Typically, SIEMs base their activities around logfiles, which by definition represent historic data. But today’s latest generation SIEM platforms can act on information pretty much as those files are written, and foremost among these systems is Exabeam.
On this episode of the Tech Means Business podcast, we speak to Bob Reny (CTO & Principal Systems Engineer) and Gareth Cox (VP Sales for Asia Pacific & Japan) from Exabeam about the company’s methodology, and how the machine learning engine at the platform’s heart works and protects.
Exabeam’s focus is very much on directed business-oriented outcomes, so it can be deployed on the basis of, for instance, “help us stop phishing attacks,” or “flag up potential insider threats.” By using advanced, self-learning algorithms, companies can be alerted to any type of anomalous activity that indicates illicit activity, even on very complex networks.
And because the learning corpus for the platform is the network it’s installed on, it improves over time for situations specific to each deployment. Up and using its smarts in weeks not months, Exabeam represents cybersecurity’s new frontier, where hackers too are leveraging AI to penetrate and destroy priceless commercial IP.
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Soon to add l33t h4kk0r to his bio, the podcast’s host Joe Green is here: