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.

Preliminary Forensics Analysis of DeepFake Images

Luca Guarnera
Primo
;
Oliver Giudice
Secondo
;
Cristina Nastasi
Penultimo
;
Sebastiano Battiato
Ultimo
2020-01-01

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.
2020
978-8-8872-3747-4
Deepfake
Generative Adversarial Networks
Multimedia Forensics
Computer Science - Computer Vision and Pattern Recognition
Computer Science - Computer Vision and Pattern Recognition
eess.IV
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/545151
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