E³ - ECR Master Class: Imaging Informatics and Artificial Intelligence

E³ 226a - Cybersecurity in AI-driven radiology systems

March 4, 10:00 - 11:00 CET

5 min
Chairperson's introduction
Anton Becker, New York City / United States
15 min
Security threats posed by AI systems in radiology
Brendan S Kelly, United Kingdom / United Kingdom
  1. To identify the cybersecurity vulnerabilities in AI-powered radiology systems.
  2. To describe how integrating AI tools into radiological workflows introduces new points of vulnerability.
  3. To evaluate the real-world of compromised cybersecurity incidents and case studies.
15 min
Can large language models (LLMs) be a security threat?
Tugba Akinci D’Antonoli, Basel / Switzerland
  1. To recognise the unique risks that LLMs introduce to radiology systems.
  2. To differentiate between traditional cybersecurity threats and those specifically associated with LLMs.
  3. To explore the mitigation strategies against LLM-related breaches.
15 min
Generative AI: identifying threats and aligning risks to data
Renato Cuocolo, Naples / Italy
  1. To examine how generative AI models can generate misleading images or manipulate patient data.
  2. To identify generative AI-related risks for regulatory and institutional environments.
  3. To propose mitigation strategies and governance controls.
10 min
Panel discussion: Dissecting a cyberattack