Visible to the public Technology of Image Steganography and Steganalysis Based on Adversarial Training

TitleTechnology of Image Steganography and Steganalysis Based on Adversarial Training
Publication TypeConference Paper
Year of Publication2020
AuthorsZhang, Han, Song, Zhihua, Feng, Boyu, Zhou, Zhongliang, Liu, Fuxian
Conference Name2020 16th International Conference on Computational Intelligence and Security (CIS)
Date Publishednov
Keywordsadversarial networks, Adversarial training, Communication networks, composability, compositionality, Computational Intelligence, convolutional neural networks, cryptography, generative adversarial networks, pubcrawl, security, steganalysis, steganography, Training
AbstractSteganography has made great progress over the past few years due to the advancement of deep convolutional neural networks (DCNN), which has caused severe problems in the network security field. Ensuring the accuracy of steganalysis is becoming increasingly difficult. In this paper, we designed a two-channel generative adversarial network (TGAN), inspired by the idea of adversarial training that is based on our previous work. The TGAN consisted of three parts: The first hiding network had two input channels and one output channel. For the second extraction network, the input was a hidden image embedded with the secret image. The third detecting network had two input channels and one output channel. Experimental results on two independent image data sets showed that the proposed TGAN performed well and had better detecting capability compared to other algorithms, thus having important theoretical significance and engineering value.
DOI10.1109/CIS52066.2020.00025
Citation Keyzhang_technology_2020