Generative Reversible Data Hiding by Image to Image Translation via GANs (Record no. 650)

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fixed length control field 01357nam a2200169 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20260901030334.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250101s2019 xx o 000 0 eng d
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Zhuo Zhang
245 10 - TITLE STATEMENT
Title Generative Reversible Data Hiding by Image to Image Translation via GANs
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE
Name of producer, publisher, distributor, manufacturer arXiv
Date of production, publication, distribution, manufacture, or copyright notice 2019
336 ## - CONTENT TYPE
Content type term text
338 ## - CARRIER TYPE
Carrier type term online resource
520 ## - SUMMARY, ETC.
Summary, etc. The traditional reversible data hiding technique is based on cover image modification which inevitably leaves some traces of rewriting that can be more easily analyzed and attacked by the warder. Inspired by the cover synthesis steganography based generative adversarial networks, in this paper, a novel generative reversible data hiding scheme (GRDH) by image translation is proposed. First, an image generator is used to obtain a realistic image, which is used as an input to the image-to-image translation model with CycleGAN. After image translation, a stego image with different semantic information will be obtained. The secret message and the original input image can be recovered separately by a well-trained message extractor and the inverse transform of the image translation. Experimental results have verified the effectiveness of the scheme.
506 0# - RESTRICTIONS ON ACCESS NOTE
Terms governing access Open access — freely available to read.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://arxiv.org/pdf/1905.02872v4">https://arxiv.org/pdf/1905.02872v4</a>
Link text Read the full paper (PDF)
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      Available online Cybersecurity Yegates University Library Yegates University Library Science and Computing 09/01/2026   YGE000911 09/01/2026 https://arxiv.org/pdf/1905.02872v4 09/01/2026 Research paper — read online