Statistical detection of information hidden in a natural image using a physical model
type: Dataset
description: With the advent of mainstream computing, the Internet and digital photography, many natural images (acquired by a camera) circulate around the world. The images are sometimes altered by a legitimate or illegal information in order to transmit confidential or secret information. In this context, steganography is a method of choice to transmit and to hide information. Therefore, it is necessary to detect the presence of hidden information in natural images. The objective of this thesis is to develop a new statistical approach to perform this detection with the highest reliability possible. As part of this work, the main challenge is to control the probability of detection error. For this purpose, a parametric model locally non-linear of a natural image is developed. This model is built from the physics of optical acquisition system and from the imaged scene. When the parameters of this model are known, a statistical test is proposed and its theoretical optimality properties are established. The main difficulty in the construction of this test is based on the fact that image pixels are always quantified. When any information on the image is not available, it is proposed to linearize the model while respecting the constraint on the probability of false alarm and guaranteeing a loss of optimality bounded. Many experiments on real images have confirmed the relevance of this new approach.
issued: 2026-05-15T20:23:37.511000
language: fr
modified: 2026-05-15T20:23:37.511006
contact point: Organization
  fn: CCSD
keyword: criminalistique
keyword: detection-et-estimation-statistiques
keyword: dissimulation-dinformation
keyword: forensique
keyword: infoeu-reposemanticsdoctoralthesis
keyword: infoinfo-itcomputer-science-csinformation-theory-csit
keyword: infoinfo-tscomputer-science-cssignal-and-image-processing
keyword: mathmath-itmathematics-mathinformation-theory-mathit
keyword: mathmath-stmathematics-mathstatistics-mathst
keyword: modele-non-lineaire
keyword: modele-parametrique
keyword: parametres-de-nuisance
keyword: signaux-non-stationnaires
keyword: spisignalengineering-sciences-physicssignal-and-image-processing
keyword: statapstatistics-statapplications-statap
keyword: statmestatistics-statmethodology-statme
keyword: statthstatistics-statstatistics-theory-statth
keyword: steganalyse
keyword: steganographie
keyword: tests-optimaux
keyword: theorie-de-linformation
keyword: theses
landing page: https://theses.hal.science/tel-00706171

Statistical detection of information hidden in a natural image using a physical model
type: Distribution
format: HTML
issued: 2026-05-15T20:23:37.529460
modified: 2026-05-15T20:23:37.473929
access URL: https://theses.hal.science/tel-00706171

test_moissonnage_selune
type: Agent