Vectra customers and security researchers respond to some of the world’s most consequential threats. Each incident requires a unique set of questions that must be answered when investigating an attack scenario.
Yet, security data today is broken and largely unable to answer these questions. It’s either incomplete or storage and performance intensive. This makes it impossible to address vital use cases that involve threat hunting, investigations, or 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.
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