Multivariate gaussian model for designing additive distortion for steganography
Jessica Fridrich, Jan Kodovský · 2013
Currently, the most successful approach to steganography in empirical objects, such as digital media, is to cast the embedding problem as source coding with a fidelity constraint. The sender specifies the costs of changing each cover element and then embeds a given payload by minimizing the total embedding cost. Since efficient practical codes exist that embed near the rate-distortion bound, the remaining task left to the steganographer is the fidelity measure - the choice of the costs. In the past, the costs were obtained either in an ad hoc manner or determined from the effects of embedding in a chosen feature space. In this paper, we adopt a different strategy in which the cover is modeled as a sequence of independent but not necessarily identically distributed quantized Gaussians and the embedding change probabilities are derived to minimize the total KL divergencewithin the chosen model for a given embedding operation and payload. Despite the simplicity of the adoptedmodel, the resulting stegosystem exhibits security that is comparable to current state-of-the-art methods methods across a wide range of payloads.