Artificial Intelligence and diagnose,reform and rewrite MRI or CT Scan report which is very much beneficial for patient but there is a bad effect of this too.Not  only  can hackers using Artificial Intelligence (AI) technology successfully and consistently trick radiologists in ways that could potentially lead to human deaths, but evildoers can even trick artificial intelligence systems designed to diagnose medical conditions based on scans.

In the recent study, the Israeli researchers used a Generative Adversarial Network (GAN), a form of machine learning system that can generate photographs that look at least superficially authentic to human observers, even though the images are nothing more than sophisticated, high-resolution computer drawings of non-existent people or landscapes.

The researchers trained one GAN to add cancer into scans that showed no cancer, and another to remove cancer from scans that showed it.  They then trained their engines to add or remove specifically lung cancer, by letting the systems learn from free online medical images.

They then hired 3 radiologists to read 100 scans: 30 authentic CT scans, and 70 that were modified by the AIs.

The results are downright scary:

The radiologists found cancer in 99 percent of the AI-altered normal scans that had malignant tumors added to them by the GAN, and found no cancer in 94 percent of the images from scans that showed cancer, but which had the cancer removed by the second GAN.

Even after the researchers told the radiologists about the GANS, and informed the doctors that many of the images had been tampered with, the radiologists were still unable to diagnose correctly, and incorrectly found cancer in 60 percent of the normal scans to which tumors had been artificially added, and did not find cancer in 87 percent of the scans from which the AI had removed tumors.

Artificial Intelligence systems designed to diagnose diseases from scans did not fare any better.

How hard would it be for an evildoer to manipulate images in order to perpetuate insurance fraud, or to inflict physical harm to another human being?

For insiders who have access to the imaging systems, such crimes would likely be simple to carry out. But, even for outsiders, the barriers are quite weak: While many MRI and CT scan systems are not connected to the Internet, getting physical access to the terminals used to manage images from these systems is not difficult.  Whether by putting on a lab coat and impersonating a doctor, pretending to be an IT support person fixing a computer, or through a whole host of other social engineering type acts, it is not hard to get access to relevant hospital terminals for long enough to insert a device into a USB port. And, of course, as time progresses, a growing number of systems are, in fact, connected to the Internet – creating the potential for remote attacks. Of course, hospital WiFi networks may serve as a potential entry point as well.

Clearly, the entire medical imaging ecosystem needs better security.

Requiring the use of security software on any device that is any way involved in the imaging process, as well as mandating that all imaging systems  use encryption and digital checksums (and/or watermarks) on images, and securing the infrastructure used by imaging-related processes, might go a long way in preventing what otherwise could ultimately emerge as a potential way to commit all sorts of crimes – even murder.