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How Machine Learning Models Can Uncover the True Causes Behind Breaches

How Machine Learning Models Can Uncover the True Causes Behind Breaches

Organizations around the world are shoring up their security with huge investments in endpoint, cloud, network and XDR solutions. But many are still grappling with a stagnant, reactive security posture.  

Why? They’re missing one key capability. 

Without an effective way to investigate and block threats, SOC analysts shift their focus to the vulnerabilities and threats that were missed. A more proactive, future-focused approach lies in understanding the type of threats that cause a breach and the data behind that. 

Join Michael Roytman, Chief Data Scientist at Kenna Security at Cisco for a meaningful, fact-based breakdown of how machine-learning techniques can help SOC analysts better analyze and decipher the millions of alerts they see in a day, and to find the alerts that matter most, faster. 

Register to learn: 

  • How XDR solutions can leverage next-generation data science, predictive analytics, and threat intelligence techniques to find the threats that matter most 
  • Why viewing XDR data through the lens of risk helps you increase efficiency and ROI, and cuts down on alerts that don’t deserve your attention 
  • Why marrying more comprehensive and enriched data sets with the promise of XDR is our best bet at modernizing the SOC

Earn one CPE credit through ISC² by attending this webinar.

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