MMCRJul 26, 2016

Natural Steganography: cover-source switching for better steganography

arXiv:1607.07824v16 citations
Originality Incremental advance
AI Analysis

This addresses the challenge of secure data hiding in digital images, offering an incremental improvement by explaining existing heuristics.

The paper tackles the problem of steganographic detection by proposing a new scheme that switches between cover sources to embed payloads, resulting in large and undetectable payloads in images.

This paper proposes a new steganographic scheme relying on the principle of cover-source switching, the key idea being that the embedding should switch from one cover-source to another. The proposed implementation, called Natural Steganography, considers the sensor noise naturally present in the raw images and uses the principle that, by the addition of a specific noise the steganographic embedding tries to mimic a change of ISO sensitivity. The embedding methodology consists in 1) perturbing the image in the raw domain, 2) modeling the perturbation in the processed domain, 3) embedding the payload in the processed domain. We show that this methodology is easily tractable whenever the processes are known and enables to embed large and undetectable payloads. We also show that already used heuristics such as synchronization of embedding changes or detectability after rescaling can be respectively explained by operations such as color demosaicing and down-scaling kernels.

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