Understanding UEBA: How machine learning helps to secure your business

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Although cyberattacks have become increasingly dangerous over the last few years, cybersecurity has seen striking developments as well. Sophisticated malicious attacks can now be stopped by defense systems that use user and entity behavior analytics (UEBA).

UEBA solutions use machine learning (ML) algorithms to learn on their own, and the ability of these solutions to defend against cyberthreats increases as they gain experience. A "normal profile" is first established for each user or entity in an environment based on their typical behaviors. Each action performed by a user or entity is compared to their "normal profile" to determine if the action is an anomaly that warrants investigation.

Many organizations use traditional security information and event management (SIEM) solutions. You can integrate your SIEM solution with your UEBA solution to further strengthen your security posture.

In this white paper, you'll learn:

  • How a multi-layered defense strategy that includes both UEBA and SIEM safeguards businesses.
  • The benefits of using UEBA.
  • Determining your risk appetite and working with risk scores.
  • How UEBA works under the hood to discover unknown threats.
  • The different anomalous behaviors of users and entities.
  • Use cases and examples of UEBA.
  • Future developments in UEBA.

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