AI Case Study

Researchers at Ben-Gurion University of the Negev are developing a system to monitor cybersecurity threats for medical equipment

Researchers at Ben-Gurion University of the Negev are developing a model to detect cyberattacks and malicious activity directed at medical instruments connected to the internet. The system is in development stages, but monitors for anomalies based on normal scan command protocols and alerts the user before a command is executed.

Industry

Healthcare

Healthcare Equipment And Supplies

Project Overview

"BGU's model uses AI to learn to recognize typical imaging scan protocols, and to predict if a new, unseen command is legitimate or not, the release said. The system can detect malicious commands from hackers, and alert the operator, before the command is executed. Next steps will be to collect more scans from different devices and sites to create a more accurate model."

Reported Results

"While the system is not yet complete, early results show a "significant milestone" in work to secure medical imaging devices, according to Mahler."

Technology

Details undisclosed

Function

Information Technology

Security

Background

"As more hospitals connect medical imaging equipment to the internet, the risk of malicious cyberattacks increases exponentially. In a Tuesday presentation at the Radiological Society of North America Annual Meeting in Chicago, BGU researcher Tom Mahler demonstrated how a hacker could bypass the security mechanisms in a CT machine and manipulate its behavior. CT machines use ionizing radiation, so changes to the dose could impact image quality, or even be harmful to the patient, the release noted."

Benefits

Data

Imaging scan protocols