Influence des Vecteurs Caractéristiques en Stéganalyse par Séparateurs à Vastes Marges

- Le but de l'analyse stéganographique est de prouver la présence d'une information cachée dans un signal hôte. Cette étude se focalise sur une analyse stéganographique aveugle des images numériques utilisant des Séparateurs à Vastes Marges (SVM). Dans un premier temps nous décrivons cette méthode de stéganalyse puis nous étudions plusieurs prédicteurs utilisés dans la phase d'extraction de caractéristiques. Enfin nous dégageons des propriétés statistiques et texturelles qui permetteront d'améliorer les performances des classificateurs à vaste marge

A Feature Selection Methodology for Steganalysis

International audienceThis paper presents a methodology to select features before training a classifier based on Support Vector Machines (SVM). In this study 23 features presented in [1] are analysed. A feature ranking is performed using a fast classifier called K-Nearest-Neighbours combined with a forward selection. The result of the feature selection is afterward tested on SVM to select the optimal number of features. This method is tested with the Outguess steganographic software and 14 features are selected while keeping the same classification performances. Results confirm that the selected features are efficient for a wide variety of embedding rates. The same methodology is also applied for Steghide and F5 to see if feature selection is possible on these scheme

Improving LSB Steganalysis using marginal and joint probabilistic distributions

International audienceThe goal of steganalysis is to search for the presence of hid- den information in numerical contents. This paper is based on a previous LSB steganalysis scheme for digital images that estimates the size of the hidden message. The accuracy of this algorithm is first outlined, then the lim- its are presented in order to introduce some solutions based on texture processing: analysis of histograms and coocur- rence matrices are presented and their uses, to improve ste- ganalysis using segmentation, is proposed1

Plasma lysosphingolipids in GRN-related diseases: Monitoring lysosomal dysfunction to track disease progression

International audienceGRN mutations are among the main genetic causes of frontotemporal dementia (FTD). Considering the progranulin involvement in lysosomal homeostasis, we aimed to evaluate if plasma lysosphingolipids (lysoSPL) are increased in GRN mutation carriers, and whether they might represent relevant fluid-based biomarkers in GRN-related diseases. We analyzed four lysoSPL levels in plasmas of 131 GRN carriers and 142 non-carriers, including healthy controls and patients with frontotemporal dementias (FTD) carrying a C9orf72 expansion or without any mutation. GRN carriers consisted of 102 heterozygous FTD patients (FTD-GRN), three homozygous patients with neuronal ceroid lipofuscinosis-11 (CLN-11) and 26 presymptomatic carriers (PS-GRN), the latter with longitudinal assessments. Glucosylsphingosin d18:1 (LGL1), lysosphingomyelins d18:1 and isoform 509 (LSM18:1, LSM509) and lysoglobotriaosylceramide (LGB3) were measured by electrospray ionization-tandem mass spectrometry coupled to ultraperformance liquid chromatography. Levels of LGL1, LSM18:1 and LSM509 were increased in GRN carriers compared to non-carriers (p < 0.0001). No lysoSPL increases were detected in FTD patients without GRN mutations. LGL1 and LSM18:1 progressively increased with age at sampling, and LGL1 with disease duration, in FTD-GRN. Among PS-GRN carriers, LSM18:1 and LGL1 significantly increased over 3.4-year follow-up. LGL1 levels were associated with increasing neurofilaments in presymptomatic carriers. This study evidences an age-dependent increase of β-glucocerebrosidase and acid sphingomyelinase substrates in GRN patients, with progressive changes as early as the presymptomatic phase. Among FTD patients, plasma lysoSPL appear to be uniquely elevated in GRN carriers, and thus might serve as suitable non-invasive disease-tracking biomarkers of progression, specific to the pathophysiological process. Finally, this study might add lysoSPL to the portfolio of fluid-based biomarkers, and pave the way to disease-modifying approaches based on lysosomal function rescue in GRN diseases