English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

The distortion in steganography that usually comes from the modification orrecoding on the cover image during the embedding process leaves thesteganalyzer with possibility of discriminating. Faced with such a risk, wepropose generative steganography with Kerckhoffs' principle (GSK) in thisletter. In GSK, the secret messages are generated by a cover image using agenerator rather than embedded into the cover, thus resulting in nomodifications in the cover. To ensure the security, the generators are trainedto meet Kerckhoffs' principle based on generative adversarial networks (GAN).Everything about the GSK system, except the extraction key, is public knowledgefor the receivers. The secret messages can be outputted by the generator if andonly if the extraction key and the cover image are both inputted. In thegenerator training procedures, there are two GANs, Message- GAN and Cover-GAN,designed to work jointly making the generated results under the control of theextraction key and the cover image. We provide experimental results on thetraining process and give an example of the working process by adopting agenerator trained on MNIST, which demonstrate that GSK can use a cover imagewithout any modification to generate messages, and without the extraction keyor the cover image, only meaningless results would be obtained.

Generative Steganography with Kerckhoffs' Principle