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How to Catch a Villian With Math

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Manage episode 275522240 series 2808508
Content provided by Microsoft. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Microsoft or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, hosts Nic Fillingham and Natalia Godyla speak with Mike Flowers and Cole Sodja of the Microsoft Protection Team, and Justin Carroll of the Microsoft Threat Intelligence Global Engagement and Response team, about how they’re using machine learning to identify and model lateral movement attacks.

Then they speak to Dr. Anna Bertiger, Senior Applied Scientist at Microsoft, on how she’s using math to catch villains and make computer networks safer.

In This Episode, You Will Learn:

  • What are lateral movement attacks
  • How machine learning helps address security challenges
  • Why grouping attack data can help better prevent threats
  • How math is used to help analyze attack trends
  • How AI and ML help identify patterns that can stop attacks

Some Questions We Ask:

  • What are the most challenging parts of identifying lateral movement attacks?
  • How does machine learning help understand how attacks would happen in the future?
  • How do attackers change techniques as security techniques change?
  • How do you use math to determine if an action is dangerous or benign?
  • What is so beautiful about math?

Resources:

Microsoft Security Blog

Mike, Cole & Justin’s Blog Post


Related:

Listen to: Afternoon Cyber Tea with Ann Johnson

Listen to: Security Unlocked: CISO Series with Bret Arsenault

Discover and follow other Microsoft podcasts at microsoft.com/podcasts


Security Unlocked is produced by Microsoft and distributed as part of The CyberWire Network.



Hosted on Acast. See acast.com/privacy for more information.

  continue reading

59 episodes

Artwork

How to Catch a Villian With Math

Security Unlocked

45 subscribers

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Manage episode 275522240 series 2808508
Content provided by Microsoft. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Microsoft or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

In this episode, hosts Nic Fillingham and Natalia Godyla speak with Mike Flowers and Cole Sodja of the Microsoft Protection Team, and Justin Carroll of the Microsoft Threat Intelligence Global Engagement and Response team, about how they’re using machine learning to identify and model lateral movement attacks.

Then they speak to Dr. Anna Bertiger, Senior Applied Scientist at Microsoft, on how she’s using math to catch villains and make computer networks safer.

In This Episode, You Will Learn:

  • What are lateral movement attacks
  • How machine learning helps address security challenges
  • Why grouping attack data can help better prevent threats
  • How math is used to help analyze attack trends
  • How AI and ML help identify patterns that can stop attacks

Some Questions We Ask:

  • What are the most challenging parts of identifying lateral movement attacks?
  • How does machine learning help understand how attacks would happen in the future?
  • How do attackers change techniques as security techniques change?
  • How do you use math to determine if an action is dangerous or benign?
  • What is so beautiful about math?

Resources:

Microsoft Security Blog

Mike, Cole & Justin’s Blog Post


Related:

Listen to: Afternoon Cyber Tea with Ann Johnson

Listen to: Security Unlocked: CISO Series with Bret Arsenault

Discover and follow other Microsoft podcasts at microsoft.com/podcasts


Security Unlocked is produced by Microsoft and distributed as part of The CyberWire Network.



Hosted on Acast. See acast.com/privacy for more information.

  continue reading

59 episodes

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