Fake Cancerous Nodes in CT Scans, Created By Malware, Trick Radiologists (washingtonpost.com)

Researchers in Israel created malware to draw attention to serious security weaknesses in medical imaging equipment and networks. An anonymous reader shares a report: Researchers in Israel say they have developed malware to draw attention to serious security weaknesses in critical medical imaging equipment used for diagnosing conditions and the networks that transmit those images -- vulnerabilities that could have potentially life-altering consequences if unaddressed. The malware they created would let attackers automatically add realistic, malignant-seeming growths to CT or MRI scans before radiologists and doctors examine them. Or it could remove real cancerous nodules and lesions without detection, leading to misdiagnosis and possibly a failure to treat patients who need critical and timely care.

Yisroel Mirsky, Yuval Elovici and two others at the Ben-Gurion University Cyber Security Research Center in Israel who created the malware say that attackers could target a presidential candidate or other politicians to trick them into believing they have a serious illness and cause them to withdraw from a race to seek treatment. The research isn't theoretical. In a blind study the researchers conducted involving real CT lung scans, 70 of which were altered by their malware, they were able to trick three skilled radiologists into misdiagnosing conditions nearly every time. In the case of scans with fabricated cancerous nodules, the radiologists diagnosed cancer 99 percent of the time. In cases where the malware removed real cancerous nodules from scans, the radiologists said those patients were healthy 94 percent of the time.

Comments

Sad commentary on humanity

[presidenteloco]

That we have to protect all technology against psychopathic super-assholes.

Is there an anti-fakery AI as well?

[az-saguaro]

Look at the demo video at: https://www.youtube.com/watch?... .

As someone who looks at such things for a living, I find this interesting but not so compelling. For the example of just a single injected nodule, I thought it looked unnatural. But, how it is perceived depends on how it is presented. Suppose they presented the images to real radiologists this way, "You will be looking at films that might be real or might be faked, guess which is which", then I think that most radiologists would know that the single nodule was not natural. But, if presented this way, "Look at these films and see if there is anything abnormal", then many would have fallen for it. But likewise many would have been thinking, "It is probably cancer, because it is a solid nodule, but it looks rather odd."

In comparison, the 472 nodule example was obviously fake. The nodules were all far too similar, too round, too uniform, too dense. I doubt many radiologists would have fallen for that.

If the authors intent was to show that fake imagery can be made that could be used for nefarious deception, then I think we already knew of that concern. I would say that I have seen far more credible and persuasive false CGI than what was seen here. If Pixar for example decided to make fake x-rays, I suspect they could do a much better job of it.

This brings up a question that seems far more interesting to me. If an AI agent can make a fake image that can fool some experts under certain conditions, but the fakery can also be recognized, then can there be a second AI agent that can spot the fakery created by the first AI?

What do you think?

Re:SO let me get this straight.

[EndlessNameless]

I'm pretty sure the studies are trying to demonstrate that their modifications are plausible and undetectable. The idea that you get bad conclusions from bad data... that's not really up for debate.

Basically, you can fool anyone with good fakes, but not everyone can make good fakes. These guys proved they can. And they have an automated tool that can do it