Privacy-Enhancing Technologies (PET) for Health Applications

• Manolis Terrovitis (ATHENA RC)

This webinar introduces the key privacy challenges arising from machine learning and data-intensive applications. Participants will explore the principles of data anonymisation, pseudonymisation, and differential privacy, along with common privacy attacks targeting datasets and AI models. The session also examines how privacy risks can be assessed and mitigated when developing compliant and privacy-preserving AI solutions.

Data Anonymization – Hands-on with Amnesia

• Manolis Terrovitis (ATHENA RC)

This hands-on session provides practical experience with data anonymisation using the Amnesia anonymisation platform (https://amnesia.openaire.eu). Through practical examples, participants will learn how anonymisation techniques can be applied in practice to reduce privacy risks and support the development of privacy-preserving data workflows.