CYBERSEC 520
Applying Machine Learning to Advance Cybersecurity
Michael P. Roman
Description from DukeHub
This course is designed to provide students hands on experience with machine learning, particularly in cybersecurity applications. This course will delve into the historical, current, and future applications of this technology in broad domains, including network defense and disinformation campaigns. Students will learn about state-of-the-art techniques being deployed today in security products, as well as burgeoning research areas for future growth. Students will also be exposed to the adversarial mindset and introduced to techniques seeking to disrupt defensive machine learning applications.
Skills
- ai and machine learningtitle: "machine learning"
AI-resilient: 0 of 5
- No: Physical, lab or field work
- No: Live work with people
- No: Judgment someone is accountable for
- No: A craft you practice with your hands or body
- No: Small, in-person format
The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works
More in CYBERSEC
- Mid-Program Residency CYBERSEC 505
- Managing Cyber Threats through Effective Leadership Strategies CYBERSEC 521
- Identity and Access Management CYBERSEC 530
- The Human Element in Cybersecurity CYBERSEC 531
- AI Security Advanced Applicati CYBERSEC 590-01
- Grc Architectures: Cybersecuri CYBERSEC 590-03