With the use of deep learning, researchers Yisroel Mirsky, Tom Mahler, Ilan Shelef and Yuval Elovici at Cyber Security Labs at Ben-Gurion University demonstrated in a video proof of concept (PoC) that an attacker could fool three expert radiologists by falsifying CT scans, inserting or removing lung cancer, the Washington Post reported.
“In 2018, clinics and hospitals were hit with numerous cyber attacks leading to significant data breaches and interruptions in medical services,”
“In 2018, clinics and hospitals were hit with numerous cyber attacks leading to significant data breaches and interruptions in medical services,” the researchers wrote. “Attackers can alter 3D medical scans to remove existing, or inject non-existing medical conditions. An attacker may do this to remove a political candidate/leader, sabotage/falsify research, perform murder/terrorism, or hold data ransom for money.”
Using a test dummy to highlight the vulnerabilities in picture archiving and communication systems (PACS), researchers demonstrated that 98% of the times they injected or removed solid pulmonary nodules, they were able to fool radiologists and state-of-the-art artificial intelligence (AI).