Scientists have invented a tool to spot deepfakes by looking at the reflections in a person's eyes, and they claim it's 94% effective

• Researchers built a tool for detecting deepfake images of people that they said was 94% effective.
• The tool looked at reflections in both of a person's eyes to figure out if the image was fake.
• Deepfaked images were more likely to have unmatched reflections, researchers found.

Researchers at the University of Buffalo have invented an ingenious new tool for spotting super-realistic "deepfake" images of people.

In a research $4 spotted by $4, researchers detailed how they built a method for spotting when a picture of a person has been generated by deepfake technology by looking closely at the eyes in the image.

The researchers found that in real photos of people, reflections in a person's corneas tended to be identical. In deepfaked images, however, the reflections were often different. When testing their tech out on deepfake-generated faces, the researchers found it was 94% effective.

There were limitations - the tool was less effective on pictures that weren't in portrait, as these photos are less likely to have visible reflections in people's eyes, researchers said.

$4 are pictures that have been digitally doctored or generated using a kind of AI technology called generative adversarial networks - or GANs. Deepfake software can be used to alter videos or images to replace a person's face with somebody else's.

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Recently, a Tom Cruise impersonator on video-sharing app TikTok $4 as the "Mission: Impossible" actor.

Deepfake tech can also be used to fabricate human faces out of thin air. In 2019 the website $4 illustrated how $4.

Many deepfake-generated images are visibly fake, but demand has increased for automated methods of detecting them as they grow more and more sophisticated.

Companies including $4 have launched deepfake-detection technologies.