AI in Radiology: New Cybersecurity Report Exposes Growing Threats

Summary

• Vital tech under threat: AI tools that are changing radiology can be attacked.
• LLMs face scrutiny: Large language models used in medical AI are a growing target.
• Variety of exploitations: Manipulated data can lead to wrong diagnoses.
• Urgent calls for action: The report calls for more security investment in healthcare AI.
• Collaborative defense strategies: Radiologists and security teams need to work together.

AI in radiology and its risks

Artificial Intelligence (AI) is changing radiology by analyzing complex medical images and data quickly. It also creates new security risks. A new report looks at those threats and what hospitals should do about them.

Where the weaknesses are

AI helps radiologists reach fast, accurate diagnoses by working through large amounts of medical data. But AI systems, especially those built on Large Language Models (LLMs), also widen the attack surface.

LLMs are increasingly used in radiology because they can pull together information from many sources. If they are manipulated, though, they can contribute to serious medical errors, which raises both safety and ethical concerns.

Types of attack

The report describes several weaknesses. One is data poisoning, where attackers feed misleading inputs that skew an AI system’s decisions. That could produce wrong readings of scans, leading to misdiagnosis and the wrong treatment.

Another is model inversion. With this technique, attackers can reconstruct private patient information from an AI model, undermining confidentiality.

Hospitals hold extremely private data. Their job includes protecting it, not only getting diagnoses right.

What the report recommends

The report calls for real investment in security for healthcare AI systems.

It is not only a job for technical teams. Radiologists and security professionals need to work together, using measures such as strong encryption and secure, ethical AI design.

Some healthcare organizations have started investing in defenses. As threats change, those defenses need constant attention.

What to watch

AI opens big possibilities in radiology. The report’s warning is that security has to keep pace.

Watch for guidance from medical and regulatory bodies on securing clinical AI, and for hospitals adding AI systems to their security testing.

Frank Jones, CISSP

Frank Jones has loved computers from the age of 13. Frank got his hacking career started when he downloaded a war dialing program that he used to detect dial up modems in his hometown of Chicago. Frank Jones now works as a JAVA coder and cyber security researcher.