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Cloud Security Podcast by Google

Jan 31, 2022


  • Elie Bursztein, security, anti-abuse and privacy researcher @ Google


  • This episode draws on a talk available in the podcast materials. Could you summarize the gist of your talk for the audience?
  • What makes the malicious document problem a good candidate for machine learning (ML)? Could you have used rules?
  • “Millions of documents in milliseconds,” not sure how to even parse it - what is involved in making it work?
  • Can you explain to the listeners the motivation for reanalyzing old samples, what ground truth means in ML/detection engineering, and how you are using this technique?
  • How fast do the attackers evolve and does this throw ML logic off?
  • Do our efforts at cat-and-mouse with attackers make the mice harder for other people to catch?  Does massive-scale ML detections accelerate the attacker's evolution?