Automated Real Time Threat Detection with Behavioral Analytics

Cybersecurity experts all agree, that in most cases, the data necessary to detect an insider or cyber attack is already being captured by the organization. After virtually every breach and compromise, digital forensics are able to reconstruct the actions of the persons or entities involved based on exisiting logs and data. 

Forensics by definition is too late!

Automated Behavioral Analytics and machine learning can detect threats as they are unfolding in real time, leveraging those same logs and data. Finding threats before the damage is done is critical, and only through the use of signatureless and automated analysis can this be accomplished consistently.

View our for a User and Entity Behavioral Analytics (UEBA) on-demand webcast. Principal Architect and Industry expert, David Swift, will discuss key use cases and capabilities.

Attendees of this webcast will learn about:

• Advanced techniques to automate discovery of Insider Threat
• Machine learning of normal behavior and detection of changes in order to reveal compromised accounts and systems
• User and Entity Behavioral Analytics (UEBA)