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Generative Information Hiding Method Based on Adversarial Networks

  • Zhuo ZhangEmail author
  • Guangyuan Fu
  • Jia Liu
  • Wenyu Fu
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 905)

Abstract

Traditional Steganography need to modify the carrier image to hide information, which will leave traces of rewriting, then eventually be perceived by the enemy. In this paper, an information hiding scheme based on Auxiliary Classifier Generative Adversarial Networks (AC-GANs) model is proposed for Steganography. This method designs and trains the networks model based on AC-GANs by constructing a dedicated dictionary and image database. The sender can map the secret information into the category labels through the dictionary, and then use the labels generate the real looking images to be sent through the model. On the contrary, the receiver can identify the image label through the model and obtain the secret information. Through experiments, the feasibility of this method is verified and the reliability of the algorithm is analyzed. This method transmits secret messages by generating images without overwriting the carrier images. It can effectively solve the problem of modification of carrier images in traditional information hiding.

Keywords

Steganography Information hiding AC-GANs GAN 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Xi’an High-Tech InstituteXi’anChina
  2. 2.Key Lab of Networks and Information Security of PAPXi’anChina
  3. 3.China Huadian Corporation LTD Sichuan Baozhusi Hydropower PlantGuangyuanChina

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