Abstract
AbstractTo fundamentally resist the steganalysis, coverless information hiding has been proposed, and it has become a research hotspot in the field of covert communication. However, the current methods not only require a huge image database, but also have a very low hidden capacity, making it difficult to apply practically. In order to solve the above problems, we propose a coverless information hiding method based on the generation of anime characters, which first converts the secret information into an attribute label set of the anime characters, and then uses the label set as a driver to directly generate anime characters by using the generative adversarial networks (GANs). The experimental results show that compared with the current methods, the hidden capacity of the proposed method is improved by nearly 60 times, and it also has good performance in image quality and robustness.
Funder
National Key R&D Program of China
National Natural Science Foundation of China
Jiangsu Basic Research Programs-Natural Science Foundation
Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD) fund
Collaborative Innovation Center of Atmospheric Environment and Equipment Technology (CICAEET) fund
Publisher
Springer Science and Business Media LLC
Subject
Electrical and Electronic Engineering,Information Systems,Signal Processing
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