Forensics Through Stega Glasses: the Case ...
Type de document :
Communication dans un congrès avec actes
Titre :
Forensics Through Stega Glasses: the Case of Adversarial Images
Auteur(s) :
Bonnet, Benoît [Auteur]
Creating and exploiting explicit links between multimedia fragments [LinkMedia]
Furon, Teddy [Auteur]
Creating and exploiting explicit links between multimedia fragments [LinkMedia]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Creating and exploiting explicit links between multimedia fragments [LinkMedia]
Furon, Teddy [Auteur]
Creating and exploiting explicit links between multimedia fragments [LinkMedia]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la manifestation scientifique :
ICPR-MMForWILD 2020 - Workshop MultiMedia FORensics in the WILD
Ville :
Milan
Pays :
Italie
Date de début de la manifestation scientifique :
2021-01-10
Titre de la revue :
Pattern Recognition: ICPR International Workshops and Challenges
Éditeur :
Springer International Publishing
Date de publication :
2021-01
Mot(s)-clé(s) en anglais :
Adversarial Examples
Steganography
Image Forensics
Steganography
Image Forensics
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Résumé en anglais : [en]
This paper explores the connection between forensics, counterforensics, steganography and adversarial images. On the one hand, forensicsbased and steganalysis-based detectors help in detecting adversarial perturbations. ...
Lire la suite >This paper explores the connection between forensics, counterforensics, steganography and adversarial images. On the one hand, forensicsbased and steganalysis-based detectors help in detecting adversarial perturbations. On the other hand, steganography can be used as a counterforensics strategy and helps in forging adversarial perturbations that are not only invisible to the human eye but also less statistically detectable. This work explains how to use these information hiding tools for attacking or defending computer vision image classification. We play this cat and mouse game using both recent deep-learning content-based classifiers, forensics detectors derived from steganalysis, and steganographic distortions dedicated to color quantized images. It turns out that crafting adversarial perturbations relying on steganographic perturbations is an effective counter-forensics strategy.Lire moins >
Lire la suite >This paper explores the connection between forensics, counterforensics, steganography and adversarial images. On the one hand, forensicsbased and steganalysis-based detectors help in detecting adversarial perturbations. On the other hand, steganography can be used as a counterforensics strategy and helps in forging adversarial perturbations that are not only invisible to the human eye but also less statistically detectable. This work explains how to use these information hiding tools for attacking or defending computer vision image classification. We play this cat and mouse game using both recent deep-learning content-based classifiers, forensics detectors derived from steganalysis, and steganographic distortions dedicated to color quantized images. It turns out that crafting adversarial perturbations relying on steganographic perturbations is an effective counter-forensics strategy.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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