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Vectra customers and security researchers respond to some of the world’s most consequential threats. And they tell us that there’s a consistent set of questions they must answer when investigating any attack scenario.Yet, security data today is broken and unable to effectively answer those questions. It is either incomplete or storage and performance intensive. Most teams don’t have the information necessary to properly answer the questions required to support their use cases; whether it be for threat hunting, investigations or supporting custom tools and models.In this session, hear about real-world use cases where security teams use machine learning engines to derive unique security attributes and how it is embedded into security workflows.
Speaker(s)
Kevin Sheu, Vectra
Slides PDF link - https://conf.splunk.com/files/2019/slides/SEC2589.pdf?podcast=1577146230
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