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.
Origine : Fichiers produits par l'(les) auteur(s)
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