Deepfakes are photos, videos or audio clips altered using AI to appear authentic, which experts have warned can mislead or be completely false.

The scientists said their team worked with Michigan State University to create software that reverse-engineers deepfake images to figure out how they were made and where they originated.

“Our method will facilitate deepfake detection and tracing in real-world settings, where the deepfake image itself is often the only information detectors have to work with,” they said.

“This work will give researchers and practitioners tools to better investigate incidents of coordinated disinformation using deepfakes, as well as open up new directions for future research.”

Facebook’s new software runs deepfakes through a network to search for imperfections left during the manufacturing process, which the scientists say alter an image’s digital “fingerprint”.

“In digital photography, fingerprints are used to identify the digital camera used to produce an image.

“Similar to device fingerprints, image fingerprints are unique patterns left on images that can be used to identify the generative model that the image came from.”

Late last year, Microsoft unveiled software that helps spot deepfake photos or videos, adding to an arsenal of programmes designed to fight the hard-to-detect images ahead of the United States presidential election.

The company’s Video Authenticator software analyses an image or each frame of a video, looking for evidence of manipulation that could be invisible to the naked eye.