Blackbox Interpretability: Next Frontier in Adversarial ML Evasion


Posted on in Presentations

Blackbox interpretability is an emerging field of study in AI and ML. ML often incorporates millions of features, making model decision interpretation nearly impossible. Interpretability promises answers to those questions, but the bad news is that attackers can also use it to identify weak spots in your defenses. Learn how you can use it to identify when attackers have discovered your secret sauce.

Learning Objectives:
1: Understand blackbox interpretability.
2: See how attackers can leverage blackbox interpretability to evade detection (feature evasion).
3: See how defenders can leverage blackbox interpretability to identify feature evasion.


Participants
Greg Ellison

Participant

Data Scientist, Microsoft

Holly Stewart

Participant

Principal Research Manager, Microsoft

Hackers & Threats Analytics Intelligence & Response

practitioner perspectives hackers & threats endpoint security artificial intelligence & machine learning anti-malware


Topic

Subtopic


Share With Your Community