Scientists Develop Deepfake Photo Identification Tool

Computer scientists at the University of Buffalo have developed a tool that can automatically identify deepfake photos by analyzing the reflection of light in the eye.

This tool proved to be 94 percent effective in their research received at the IEEE International Conference on Acoustics, Speech and Signal Processing which will be held in June 2021 in Toronto, Canada.

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“The cornea of ​​the eye is almost like a perfect semisphere and is highly reflective,” said the paper’s lead author, Siwei Lyu, PhD, Professor of the Department of Computer Science and Engineering.

So, according to Lyu, “anything that enters the eye with light emitted from that source will have an image on the cornea.”

“The two eyes must have a very similar reflective pattern because they see the same thing. This is something we usually don’t notice when we look at faces,” said Lyu, who also has expertise in digital forensics and multimedia as quoted from a press release, via Eurekalert, Monday (15/3).

Currently, the paper entitled “Exposing GAN-Generated Faces Using Inconsistent Corneal Specular Highlights” is available in the open access arXiv repository.

The research also involved Shu Hu, a third-year PhD candidate in computer science and research assistant at the Media Forensic Lab at UB, and Yuezun Li, PhD, a former senior research scientist at UB who is currently a lecturer at the Center for Artificial Intelligence at Ocean University of China.