Machine Learning Security Workshop

Guy Barnhart-Magen

November 4, 2019

Course Objectives

At the end of the course, participants will:

Course Overview

With the explosive growth of machine learning applications and products, the question of their security touchpoint is becoming a major interest area for many organizations. Machine learning security covers both how such products affect the security posture of the organization, and what threats they bring to such a system, as well as how to protect such systems from adversaries. This course outlines the state-of-the-art in machine learning security and how the topic has evolved. It is intended for developers and managers to make strategic decisions for their machine learning products as both a vendor and a customer.

Course Duration

2-day instructor-led training

Course Outlines


Overview of Machine Learning Tasks

The Machine Learning Threat Model

Adversarial Poisoning Attacks

Adversarial Evasion Attacks

Adversarial Attacks on Malware Detection Systems

ML Differential Privacy and Model Thefts

Penetration Testing of ML models