General information
Organisation
The French Alternative Energies and Atomic Energy Commission (CEA) is a key player in research, development and innovation in four main areas :
• defence and security,
• nuclear energy (fission and fusion),
• technological research for industry,
• fundamental research in the physical sciences and life sciences.
Drawing on its widely acknowledged expertise, and thanks to its 16000 technicians, engineers, researchers and staff, the CEA actively participates in collaborative projects with a large number of academic and industrial partners.
The CEA is established in ten centers spread throughout France
Reference
SL-DRT-24-0508
Direction
DRT
Thesis topic details
Category
Technological challenges
Thesis topics
Advancing image sensor security: using deep learning for simultaneous robust and fragile watermarking
Contract
Thèse
Job description
This PhD project aims at advancing the field of image sensor security through a comprehensive exploration of recent deep learning techniques applied to both robust and fragile invisible watermarking. In the specific context of embedded image rendering pipelines, this study aims to address the dual challenges of ensuring resistance against intentional attacks to break the mark (robust watermarking) while maintaining a high sensitivity to alterations (fragile watermarking). The goal of this multifaceted design approach is not only to enhance the security of imager data but additionally opens avenues for applications in authentication, tamper and forgery detection, combined with data integrity checking. The research will delve into fields of research from image sensor rendering pipeline design using attention-augmented deep learning models to the intricacies of embedding multiple watermarks simultaneously, addressing the requirement for both robust and fragile characteristics.
This research is therefore an exciting opportunity for PhD candidates showing interest in the intersection of deep learning, image processing, and security. It provides not only a rich academic landscape for impactful scientific contributions but also holds potential for concrete results for upcoming technological transfers. In practice, the work will consists in finding novel algorithmic solutions to improve watermarking performance, designed to deal with most advanced Deep Learning based attacks, while maintaining a high image quality rendering.
University / doctoral school
Electronique, Electrotechnique, Automatique, Traitement du Signal (EEATS)
Université Grenoble Alpes
Thesis topic location
Site
Grenoble
Requester
Position start date
01/10/2024
Person to be contacted by the applicant
GUICQUERO William william.guicquero@cea.fr
CEA
DRT/DOPT//L3I
CEA leti/DOPT
Minatec Campus
17, rue des Martyrs
38054 Grenoble Cedex
04 38 78 09 57
Tutor / Responsible thesis director
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