Privacy in AI/ML and Cybersecurity

This morning session looks at privacy in machine learning: why a private dataset does not automatically produce a private model, how training data can leak, and the main defenses that address it — differential privacy, federated learning, and privacy-preserving machine learning — including what each one does and does not protect, with an eye toward how to teach these ideas in a cybersecurity classroom.