CT-GAN: Malicious Tampering of 3D Medical Imagery using Deep Learning

Understand

In 2018, clinics and hospitals were hit with numerous attacks leading to significant data breaches and interruptions in medical services.

• An attacker with access to medical records can do much more than hold the data for ransom or sell it on the black market.
• In this paper, we show how an attacker can use deep-learning to add or remove evidence of medical conditions from volumetric (3D) medical scans.
• An attacker may perform this act in order to stop a political candidate, sabotage research, commit insurance fraud, perform an act of terrorism, or even commit murder.