Title :

Combining Forensics and Privacy Requirements for Digital Images

Author(s) :

Puteaux, Pauline [Auteur]
Image & Interaction [ICAR]
Itier, Vincent [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Ecole nationale supérieure Mines-Télécom Lille Douai [IMT Lille Douai]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Conference title :

EUSIPCO 2021 - 29th European Signal Processing Conference

City :

Dublin (virtual)

Country :

Irlande

Start date of the conference :

2021-08-23

Publication date :

2021

English keyword(s) :

Forensics
Privacy
Visual confidentiality
Selective encryption
Trade-off

HAL domain(s) :

Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Cryptographie et sécurité [cs.CR]

English abstract : [en]

This paper proposes to study the impact of image selective encryption on both forensics and privacy preserving mechanisms. The proposed selective encryption scheme works independently on each bitplane by encrypting the s ...
Show more >This paper proposes to study the impact of image selective encryption on both forensics and privacy preserving mechanisms. The proposed selective encryption scheme works independently on each bitplane by encrypting the s most significant bits of each pixel. We show that this mechanism can be used to increase privacy by mitigating image recognition tasks. In order to guarantee a trade-off between forensics analysis and privacy, the signal of interest used for forensics purposes is extracted from the 8−s least significant bits of the protected image. We show on the CASIA2 database that good tampering detection capabilities can be achieved for s ∈ {3,. .. , 5} with an accuracy above 80% using SRMQ1 features, while preventing class recognition tasks using CNN with an accuracy smaller than 50%.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

Utilisation de grandes bases d'images hétérogènes en stéganalyse pour se rapprocher d'un contexte opérationnel
Outils pour la détection de manipulation d'images numériques.

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL