Title :

ALASKA-2 : Challenging Academic Research on Steganalysis with Realistic Images

Author(s) :

Cogranne, Rémi [Auteur]
Laboratoire Modélisation et Sûreté des Systèmes [LM2S]
Giboulot, Quentin [Auteur]
Laboratoire Modélisation et Sûreté des Systèmes [LM2S]
Bas, Patrick [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]

Conference title :

IEEE International Workshop on Information Forensics and Security

City :

New York City (Virtual Conference)

Country :

Etats-Unis d'Amérique

Start date of the conference :

2020-12-06

HAL domain(s) :

Informatique [cs]/Traitement des images [eess.IV]
Informatique [cs]/Traitement du signal et de l'image [eess.SP]
Informatique [cs]/Cryptographie et sécurité [cs.CR]
Informatique [cs]/Intelligence artificielle [cs.AI]
Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]

English abstract : [en]

This paper briefly summarizes the ALASKA#2 steganalysis challenge which has been organized on the Kaggle machine learning competition platform. We especially focus on the context, the organization (rules, timeline, evaluation ...
Show more >This paper briefly summarizes the ALASKA#2 steganalysis challenge which has been organized on the Kaggle machine learning competition platform. We especially focus on the context, the organization (rules, timeline, evaluation and material) as well as on the outcome (number of competitors, submission, findings, and final results). While both steganography and steganalysis were new to most of the competitors, they were able to leverage their skills in Deep Learning in order to design detection methods that perform significantly better than current art in steganalysis. Despite the fact that these solutions come at an important computational cost, they clearly indicate new directions to explore in steganalysis research.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