Anmol
Agarwal
Senior Security Researcher
"Demystifying Adversarial Machine Learning Attacks"
"Demystifying Adversarial Machine Learning Attacks"
24 - 11:10 AM EDT/New York (See in local time)
Add to Calendar
05/24/2025 11:10 AM
05/24/2025 11:30 AM
America/New_York
#WTGC2025
"Demystifying Adversarial Machine Learning Attacks"
#WTGC2025
"Demystifying Adversarial Machine Learning Attacks"
https://www.womentech.net/ringcentral
https://www.womentech.net/ringcentral
"Demystifying Adversarial Machine Learning Attacks"
"Demystifying Adversarial Machine Learning Attacks"
Don’t miss out and join visionaries, innovators, and thought leaders from all over the world at the Women in Tech Global Conference.
Vote by Sharing
Unite 100 000 Women in Tech to Drive Change with Purpose and Impact.
Do you want to see this session? Help increase the sharing count and the session visibility. Sessions with +10 votes will be available to career ticket holders.
Please note that it might take some time until your share & vote is reflected.
Session: Demystifying Adversarial Machine Learning Attacks
AI and Machine learning are being used to analyze large amounts of data. While machine learning has many benefits, machine learning is also prone to being attacked. In this session, attendees will be introduced to the idea of adversarial machine learning and attacks to machine learning models. Attendees will learn about some real-world case studies regarding attacks that have impacted top global companies in the industry as well as current open-source industry solutions that aim to increase the security of machine learning algorithms. After the session, attendees will have a better understanding of machine learning’s role in the cyber threat landscape as well as measures they can take to secure their organization’s machine learning technologies.Key Takeaways
- Be able to understand different types of adversarial machine learning attacks
- Understand how to recognize adversarial machine learning attacks in products
- Learn how to mitigate some adversarial machine learning attack risks through the use of open-source solutions
Bio
Dr. Anmol Agarwal is a security researcher specializing in AI and Machine Learning security in 5G and 6G. Dr. Agarwal holds a doctoral degree in cybersecurity analytics from George Washington University; her research focused on AI security. She has a Master's degree in computer science and a Bachelor's degree in software engineering from the University of Texas at Dallas. She previously worked at the U.S. Cybersecurity and Infrastructure Security Agency (CISA). Dr. Agarwal is also an active conference speaker and has spoken at a wide variety of conferences such as SecureWorld, Bridges in Tech, and the Pacific Hackers Conference. In her free time, Dr. Agarwal enjoys giving back to the community and is an active industry mentor. When she is not working or mentoring, she enjoys spending time with her family and traveling.