Preliminary Forensics Analysis of DeepFake Images

Abstract

One of the most terrifying phenomenon nowadays is the DeepFake: the possibility to automatically replace a person's face in images and videos by exploiting algorithms based on deep learning. This paper will present a brief overview of technologies able to produce DeepFake images of faces. A forensics analysis of those images with standard methods will be presented: not surprisingly state of the art techniques are not completely able to detect the fakeness. To solve this, a preliminary idea on how to fight DeepFake images of faces will be presented by analysing anomalies in the frequency domain.

arXiv commentAccepted at IEEE AEIT International Annual Conference 2020

References in corpus (3)

• MesoNet: a Compact Facial Video Forgery Detection Network
• Media Forensics and DeepFakes: an overview
• A Classification Engine for Image Ballistics of Social Data

Cited by in corpus (3)

• Fighting deepfakes by detecting GAN DCT anomalies
• On the Exploitation of DCT-Traces in the Generative-AI Domain
• Deepfake Style Transfer Mixture: a First Forensic Ballistics Study on Synthetic Images