Using Set Covering to Generate Databases for Holistic Steganalysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F22%3A00364282" target="_blank" >RIV/68407700:21230/22:00364282 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1109/WIFS55849.2022.9975430" target="_blank" >https://doi.org/10.1109/WIFS55849.2022.9975430</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/WIFS55849.2022.9975430" target="_blank" >10.1109/WIFS55849.2022.9975430</a>

Result language

angličtina

Original language name

Using Set Covering to Generate Databases for Holistic Steganalysis

Original language description

Within an operational framework, covers used by a steganographer are likely to come from different sensors and different processing pipelines than the ones used by researchers for training their steganalysis models. Thus, a performance gap is unavoidable when it comes to out-of-distributions covers, an extremely frequent scenario called Cover Source Mismatch (CSM). Here, we explore a grid of processing pipelines to study the origins of CSM, to better understand it, and to better tackle it. A set-covering greedy algorithm is used to select representative pipelines minimizing the maximum regret between the representative and the pipelines within the set. Our main contribution is a methodology for generating relevant bases able to tackle operational CSM. Experimental validation highlights that, for a given number of training samples, our set covering selection is a better strategy than selecting random pipelines or using all the available pipelines. Our analysis also shows that parameters as denoising, sharpening, and downsampling are very important to foster diversity. Finally, different benchmarks for classical and wild databases show the good generalization property of the extracted databases.

Czech name

—

Czech description

—

Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

—

Continuities

R - Projekt Ramcoveho programu EK

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

IEEE International Workshop on Information Forensics and Security

ISBN

979-8-3503-0967-6

ISSN

2157-4766

e-ISSN

—

Number of pages

6

Pages from-to

—

Publisher name

Institute of Electrical and Electronics Engineers, Inc.

Place of publication

—

Event location

Online

Event date

Dec 12, 2022

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

000907044000021