Published 15 March 2021 Computer scientists have developed a tool that automatically identifies deepfake photos by analyzing light reflections in the eyes. The tool proved 94 percent effective with portrait-like photos in experiments. University at Buffalo computer scientists have developed a tool that automatically identifies deepfake photos by analyzing light reflections in the eyes. The tool proved 94 percent effective with portrait-like photos in experiments described in a paper accepted at the IEEE International Conference on Acoustics, Speech and Signal Processing to be held in June in Toronto, Canada. “The cornea is almost like a perfect semisphere and is very reflective,” says the paper’s lead author, Siwei Lyu, PhD, SUNY Empire Innovation Professor in the Department of Computer Science and Engineering. “So, anything that is coming to the eye with a light emitting from those sources will have an image on the cornea.