Forensics and Analysis of Deepfake Videos

Abstract

The spread of smartphones with high quality digital cameras in combination with easy access to a myriad of software apps for recording, editing and sharing videos and digital images in combination with deep learning AI platforms has spawned a new phenomenon of faking videos known as Deepfake. We design and implement a deep-fake detection model with mouth features (DFT-MF), using deep learning approach to detect Deepfake videos by isolating, analyzing and verifying lip/mouth movement. Experiments conducted against datasets that contain both fake and real videos showed favorable classification performance for DFT-MF model especially when compared with other work in this area.