西安电子科技大学学报（自然科学版）2019，Vol.46Issue(1)：79-85,7.DOI:10.19665/j.issn1001-2400.2019.01.013
利用模块化残差网络的图像隐写分析
Image steganalysis based on the modularized residual network
摘要
Abstract
In order to improve the detection accuracy of small embedding rate steganography,an image steganalysis method based on the highly modularized convolutional neural network is proposed.First,the fundamental network is built by repeating residual network units to extract the complex statistical properties of digital images.Then,extracting the channel information on the residual image by adding the group convolution,it is very good to strengthen the signal characteristics from the hidden information.Finally,a large number of datasets are used to train the network,and the image steganalysis method based on the modularized residual network is obtained.Experimental results show that compared with the existing methods,the proposed method has a better performance,and extracts more effective image features. Meanwhile,using the residual network module as the template,the network model can be easily built to facilitate adjustment and training.关键词
隐写分析/残差网络/分组卷积/模块化/低嵌入率Key words
steganalysis/residual network/group convolution/modularized/low embedding rate分类
信息技术与安全科学引用本文复制引用
郭继昌,何艳红,魏慧文..利用模块化残差网络的图像隐写分析[J].西安电子科技大学学报（自然科学版）,2019,46(1):79-85,7.基金项目
天津市自然科学基金(15JCYBJC15500) （15JCYBJC15500）
