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:
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.
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