A Game-Theoretic Approach to Content-Adaptive Steganography

Content-adaptive embedding is widely believed to improve steganographic security over uniform random embedding. However, such security claims are often based on empirical results using steganalysis methods not designed to detect adaptive embedding. We propose a framework for content-adaptive embedding in the case of imperfect steganography. It formally defines heterogeneity within the cover as a necessary condition for adaptive embedding. We devise a game-theoretic model for the whole process including cover generation, adaptive embedding, and a detector which anticipates the adaptivity. Our solution exhibits a unique equilibrium in mixed strategies. Its location depends on the level of heterogeneity of the cover source, but never coincides with naïve adaptive embedding. The model makes several simplifying assumptions, including independent cover symbols and the steganalyst’s ability to recover the adaptivity criterion perfectly.