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• W2892881493 abstract "The distortion in steganography that usually comes from the modification or recoding of the cover image during the embedding process. And it is the embedding distortion that leaves the steganalyzer with possible discrimination. Therefore, we propose generative steganography with Kerckhoffs’ principle (GSK) in this paper. In GSK, the secret messages are generated by a cover image using a generator rather than embedded into the cover, which results in no modifications to the cover. To ensure security, the generators are trained to meet Kerckhoffs’ principle based on generative adversarial networks (GANs). Everything about the GSK system is public knowledge for the receivers, except the extraction key. The secret messages can be outputted by the generator if and only if the extraction key and the cover image are both inputted. In the generator training procedures, there are two GANs (Message-GAN and Cover-GAN) that are designed to work jointly, making the generated results under the control of the extraction key and the cover image. We provide experimental results for the training process. We present an example of the working process by adopting a generator trained on the dataset MNIST, which demonstrates that GSK can use a cover image without any modification to generate messages. Furthermore, only meaningless results would be obtained without the extraction key or the cover image." @default.
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• W2892881493 date "2018-09-24" @default.
• W2892881493 modified "2023-09-24" @default.
• W2892881493 title "Generative steganography with Kerckhoffs’ principle" @default.
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• W2892881493 doi "https://doi.org/10.1007/s11042-018-6640-y" @default.
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