Rethinking Optimal Embedding - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Communication Dans Un Congrès Année : 2016

Rethinking Optimal Embedding

Résumé

At present, almost all leading steganographic techniques for still images use a distortion minimization paradigm, where each potential change is assigned a cost ci and the change probabilities πi chosen to minimize the average total cost i πici. However, some detectors have exploited knowledge of this adaptivity and the embedding cannot be considered optimal. In this work we prove a theoretical result suggesting that, against a knowing attacker, the embedder should simply minimize i π 2 i ci instead, for the same costs ci, which is the minimax and equilibrium strategy. This aligns with some special case results that have appeared in recent literature. We then test some simple steganographic methods in theoretical and real settings, showing that naive (average cost) adaptivity is exploitable, but the equilibrium probabilities cannot be exploited. However, it is essential to determine statistically well-founded costs ci.
Fichier principal
Vignette du fichier
camera-ready (1).pdf (369.16 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01360016 , version 1 (23-10-2016)

Identifiants

Citer

Andrew Ker, Tomáš Pevný, Patrick Bas. Rethinking Optimal Embedding. 4th ACM Workshop on Information Hiding and Multimedia Security, Jun 2016, Vigo, Spain. pp.93-102, ⟨10.1145/2909827.2930797⟩. ⟨hal-01360016⟩
162 Consultations
181 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More