Machine learning is ubiquitous today. As we begin to rely on machine learning for daily tasks, threat factors will begin to target machine learning. In this session, attendees will learn about adversarial machine learning and the different kinds of attacks that target machine learning. In addition, attendees will learn about real world case studies regarding attacks that have impacted the industry as well as current industry solutions that strive to secure and mitigate attacks to machine learning.

Attendees will: 

1. Learn the difference between AI and machine learning.
2. Understand how machine learning works.
3. Be able to distinguish between the different adversarial machine learning attacks and recognize how these attacks have occurred in the industry.
4. Apply open-source industry solutions to secure machine learning.