Introduction to Adversarial Machine Learning

Machine learning is ubiquitous today. As we begin to rely on machine learning for daily tasks, threat actors 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 open-source industry solutions that strive to secure and mitigate attacks to machine learning.

Dr. Anmol Agarwal is a security researcher at a Fortune 500 Company and is focused on securing AI and Machine Learning in 5G and 6G. She holds a doctoral degree in cybersecurity analytics from George Washington University and a master's degree in computer science from the University of Texas at Dallas. She previously worked at the U.S. Cybersecurity and Infrastructure Security Agency (CISA) in the High Value Asset Program Management Office. In her free time, she enjoys giving back to the community and is an active industry mentor. She will be representing herself at this event as an individual security researcher. She is not representing her employer.