Dive into the world of machine learning security with this 38-minute conference talk by Abraham Kang, presented by the OWASP Foundation. Explore key concepts such as adversarial samples, attack goals, and various machine learning models including Naive Bayesian, Linear Classification, Decision Trees, and Random Forest. Learn about adversarial attacks, adversarial training, and the adversarial robustness toolkit to enhance your understanding of MLSec and its practical applications in cybersecurity.
Overview
Syllabus
Intro
Adversarial Samples
What Can You Attack
Goal Intuition
Attacking Procedure
Naive Bayesian
Linear Classification
Decision Trees
Random Forest
Adversarial Attacks
adversarial training
adversarial robustness toolkit
Taught by
OWASP Foundation
