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Weakening the Detecting Capability of CNN-based Steganalysis [article]

Sai Ma, Qingxiao Guan, Xianfeng Zhao, Yaqi Liu
2018 arXiv   pre-print
In this paper we propose a method to generate steganographic adversarial example in order to enhance the steganographic security of existing algorithms.  ...  However, all these kinds of back-propagation based neural networks may be cheated by forging input named the adversarial example.  ...  Given a optimized steganalytic CNN model, we can generate the adversarial examples of the input images.  ... 
arXiv:1803.10889v1 fatcat:vndpxapy7vcznh5efd5xolsfn4

Detection based Defense against Adversarial Examples from the Steganalysis Point of View [article]

Jiayang Liu, Weiming Zhang, Yiwei Zhang, Dongdong Hou, Yujia Liu, Hongyue Zha, Nenghai Yu
2018 arXiv   pre-print
In this paper, we point out that steganalysis can be applied to adversarial examples detection, and propose a method to enhance steganalysis features by estimating the probability of modifications caused  ...  However, DNNs are vulnerable to adversarial examples which are samples with imperceptible perturbations while dramatically misleading the DNNs.  ...  For a neural network with cross-entropy cost function J(X, y) where X is the input image and y t is the target class for the input image, the adversarial example is generated as X adv = X − sign(∇ X J(  ... 
arXiv:1806.09186v3 fatcat:sukqgnvhgjbebn2ynkwl3rgf6u

A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis

2020 KSII Transactions on Internet and Information Systems  
In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning.  ...  The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis.  ...  [68] has proposed another CNN based method to generate steganographic adversarial examples in order to enhance the steganographic security of exiting algorithms.  ... 
doi:10.3837/tiis.2020.03.017 fatcat:7ci7bfbjsfd2nn5yagnv2h3ora

Enhancing the Security of Deep Learning Steganography via Adversarial Examples

Yueyun Shang, Shunzhi Jiang, Dengpan Ye, Jiaqing Huang
2020 Mathematics  
In this paper, we take advantage of the linear behavior of deep learning networks in higher space and propose a novel steganography scheme which enhances the security by adversarial example.  ...  With the development of deep learning, some novel steganography methods have appeared based on the autoencoder or generative adversarial networks.  ...  Therefore, the security of steganography could be enhanced by adversarial examples techniques.  ... 
doi:10.3390/math8091446 fatcat:5ym7fu64bzd3tfhw6xgrfhqqeu

High-Capacity Robust Image Steganography via Adversarial Network

2020 KSII Transactions on Internet and Information Systems  
In the secure model, to enhance the security of the basic model, a steganalysis network has been added into the basic model to form an adversarial network.  ...  The high-capacity steganography is implemented by hiding a secret image into a carrier image having the same resolution with the help of concat operations, InceptionBlock and convolutional layers.  ...  It is better than our basic model because the adversarial network with steganalysis considered in the secure model enhances the quality of steganographic images to resist steganalysis; (b) the secure and  ... 
doi:10.3837/tiis.2020.01.020 fatcat:ko2xyinesnfklbltpslwvpvd2m

Decode and Transfer: A New Steganalysis Technique via Conditional Generative Adversarial Networks [article]

Parisa Babaheidarian, Mark Wallace
2019 arXiv   pre-print
image into a high quality RGB image with details visible to human eyes.  ...  We incorporate a deep neural network to decode an approximate estimate of the secret image followed by a domain adaptation technique based on generative adversarial networks which transfers the decoded  ...  Our simulations show that using limited examples of the steganography images, we can effectively train our steganalysis networks with fairly good generalization performance to unseen data.  ... 
arXiv:1901.09746v1 fatcat:ga3roayg2zg7pkjj3wuer5raqu

Adaptive Spatial Steganography Based on Probability-Controlled Adversarial Examples [article]

Sai Ma and Qingxiao Guan and Xianfeng Zhao and Yaqi Liu
2019 arXiv   pre-print
ACKNOWLEDGMENT The authors would like to thank the members of DDE Laboratory in SUNY Binghamton for sharing their codes and image base, and the members of MICS Laboratory in Shenzhen University for sharing  ...  With deep learning based steganalysis methods, we can enhance the security of existing steganographic methods via adversarial method.  ...  The generated steganographic adversarial example is probability-controlled, comparing with the adversarial examples generated by category-controlled.  ... 
arXiv:1804.02691v3 fatcat:q4zfofimqfhp3mdkipoavl5k7q

Adversarial Attack based on Perturbation of Contour Region to Evade Steganalysis-based Detection

Hyunsik Na, Gwonsang Ryu, Daeseon Choi
2021 IEEE Access  
Next, we detected these adversarial images using steganalysis-based detection with LDA.  ...  ADVERSARIAL ROBUSTNESS TO STEGANALYSIS-BASED DETECTION To evaluate the robustness of the adversarial examples generated through the above processes to steganalysis-based detection, we extracted the SPAM  ... 
doi:10.1109/access.2021.3109602 fatcat:oxgamzegofcz7fmkfizs7ny22i

The secure steganography for hiding images via GAN

Zhangjie Fu, Fan Wang, Xu Cheng
2020 EURASIP Journal on Image and Video Processing  
Compared with the previous steganography model for hiding color images based on deep learning, the steganography model in this article could achieve steganographic images with higher visual quality and  ...  Moreover, it utilizes the adversarial training between the encoder-decoder network and the steganalysis model to improve the ability to resist the detection of steganalysis models based on deep learning  ...  of steganalysis model by adversarial training with the encoder-decoder network.  ... 
doi:10.1186/s13640-020-00534-2 fatcat:xshude3upzgojidnqjudspgyee

FNet: A Two-Stream Model for Detecting Adversarial Attacks against 5G-Based Deep Learning Services

Guangquan Xu, Guofeng Feng, Litao Jiao, Meiqi Feng, Xi Zheng, Jian Liu, Benjamin Aziz
2021 Security and Communication Networks  
Experimental results show that our proposed method can accurately detect adversarial examples. Even with powerful attacks, we can still achieve a detection rate of 91.3%.  ...  Moreover, our method has good transferability to generalize to other adversaries.  ...  Table 7 : 7 Performance of normal images and their adversarial examples generated by CW on CIFAR-10.  ... 
doi:10.1155/2021/5395705 fatcat:uuhnldz6mfg4rizz4asfqvefnu

A Survey on Digital Image Steganography

Jiaxin Wang, Mengxin Cheng, Peng Wu, Beijing Chen
2019 Journal of Information Hiding and Privacy Protection  
.; Li, B. (2018): A novel image steganography method via deep convolutional generative adversarial networks. IEEE Access, vol. 6, pp. 38303-38314. Kekre, H. B.; Athawale, A. A.; Athawale, U.  ...  . : Data hiding in images with adaptive numbers of least significant bits based on the human visual system. Ahmad, J.; Rehman, N.  ...  [Hayes and Danezis (2017)] used adversarial learning to generate steganographic images directly. Then, Hu et al.  ... 
doi:10.32604/jihpp.2019.07189 fatcat:6dnb6vpepjfhfkl45e46pkggha

Enhancing JPEG Steganography using Iterative Adversarial Examples [article]

Huaxiao Mo, Tingting Song, Bolin Chen, Weiqi Luo, Jiwu Huang
2019 arXiv   pre-print
Convolutional Neural Networks (CNN) based methods have significantly improved the performance of image steganalysis compared with conventional ones based on hand-crafted features.  ...  In this paper, we propose a novel steganography framework based on adversarial example in an iterative manner.  ...  In [11] , Zhang et al constructed enhanced covers by adding adversarial noise to cover based on adversarial example technique.  ... 
arXiv:1909.07556v3 fatcat:5zmv3pefijgptmcdupmmpptfua

Adversarial Images through Stega Glasses [article]

Benoît Bonnet, Teddy Furon, Patrick Bas
2020 arXiv   pre-print
This paper explores the connection between steganography and adversarial images. On the one hand, ste-ganalysis helps in detecting adversarial perturbations.  ...  We play this cat and mouse game with state-of-art classifiers, steganalyzers, and steganographic embedding schemes. It turns out that steganography helps more the attacker than the defender.  ...  Top row: Cover images with their label below. Bottom row: adversarial images with steganographic embedding GINA (d=4).  ... 
arXiv:2010.07542v1 fatcat:rv27atmp4zhgvmbvx2ixnezale

A Brief Survey on Deep Learning Based Data Hiding [article]

Chaoning Zhang, Chenguo Lin, Philipp Benz, Kejiang Chen, Weiming Zhang, In So Kweon
2022 arXiv   pre-print
Finally, further insight into deep hiding is provided by incorporating the perspective of adversarial attack.  ...  Data hiding is the art of concealing messages with limited perceptual changes. Recently, deep learning has enriched it from various perspectives with significant progress.  ...  Steganography and steganalysis defeat but also enhance each other. Generally speaking, to archive being undetectable for steganalysis, targeted designs are required.  ... 
arXiv:2103.01607v2 fatcat:z4kyyy234vgltp3kpdhq5h5wsu

Emerging Applications of Reversible Data Hiding [article]

Dongdong Hou and Weiming Zhang and Jiayang Liu and Siyan Zhou and Dongdong Chen and Nenghai Yu
2018 arXiv   pre-print
In this paper, we summarize these emerging applications, including steganography, adversarial example, visual transformation, image processing, and give out the general frameworks to make these operations  ...  Usually, the image to generate adversarial example is the sensitive and important one such as military imagery, which can not be damaged with loss.  ...  The enhanced image will be displayed each time by re-enhanced the original image with the help of the record file. However, the enhanced image can be only correctly viewed on their own software.  ... 
arXiv:1811.02928v1 fatcat:mhboz2n53nfjpnx4takvs46s5q
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