Jan 31, 2022
Guest:
- Elie Bursztein, security, anti-abuse and privacy researcher @ Google
Topics:
- 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?
Resources: