National Natural Science Foundation of China (Grant Nos. 62172435, 62202495, and U2336206);National Key Research and Development Program of China (Grant No. 2022 YFB3102900);Zhongyuan Science and Technology Innovation Leading Talent Project, China (Grant No. 214200510019);Key Research and Development Project of Henan Province (Grant No. 221111321200)。
Existing deep learning-based steganography detection methods utilize convolution to automatically capture and learn steganographic features, yielding higher detection efficiency compared to manually designed steganogr...
supported by the National Natural Science Foundation of China (61872368, 61802410)。
Deep learning based language models have improved generation-based linguistic steganography,posing a huge challenge for linguistic steganalysis.The existing neural-network-based linguistic steganalysis methods are inc...
supported by National Natural Science Foundation of China(U1736118,U2001202,62072480);the Key Areas R&D Program of Guangdong(2019B010136002).
Residual computation is an effective method for gray-scale image steganalysis.For binary images,the residual computation calculated by the XOR operation is also employed in the local residual patterns(LRP)model for st...
supported by the National Natural Science Foundation of China(No.61402115,No.u1536115,No.u1536207)
As wavelet packet transform is able to focus on minute change of signals, this study proposes an analytic approach of low embedding steganograpy based on high order Histogram moments in frequency domain(HMFD), which p...
This work is supported by the National Key Basic Research Program of China (No.2007CB310801), the Major Research Project of National Natural Science Foundation of China (No.90718006) and the Ph.D. Programs Foundation of Ministry of Education of China (No.20070486107).
MB1 is a very promising steganography and few steganalysis methods have been proposed to attack MB1 so far. In this paper, we propose a specific steganal- ysis method which can effectively break MB1 steganogra- phy. W...
This work is supported by the National Natural Science Foundation of China (No.60572111). Hui for many useful of this paper. The authors would like to thank the reviewers for their careful reading and insightful comments. Special thanks belong to Shen Linjie, Wang Bo and Song Hui for many useful discussions during preparation of this paper.
The objective of quantitative steganalysis is to achieve reliable estimation of embedded message length of a suspected digital object. This type of methods has received considerable attention due to its capability of ...
Jsteg is an open steganography software on Internet. It uses the LSB of DCT coefficients to hide secret information in image. Chi-square attack can detect sequential Jsteg hiding but it can't detect the random Jsteg ...