25.3.10.2 Data Hiding, Steganography, Adversarial Networks, Convolutional Networks, Deep Learning

Xu, G., Wu, H.Z., Shi, Y.Q.,
Structural Design of Convolutional Neural Networks for Steganalysis,
SPLetters(23), No. 5, May 2016, pp. 708-712.
IEEE DOI 1604
Computer architecture BibRef

Tang, W., Tan, S., Li, B., Huang, J.,
Automatic Steganographic Distortion Learning Using a Generative Adversarial Network,
SPLetters(24), No. 10, October 2017, pp. 1547-1551.
IEEE DOI 1710
steganography, automatic steganographic distortion learning, BibRef

Li, B., Wei, W., Ferreira, A., Tan, S.,
ReST-Net: Diverse Activation Modules and Parallel Subnets-Based CNN for Spatial Image Steganalysis,
SPLetters(25), No. 5, May 2018, pp. 650-654.
IEEE DOI 1805
feedforward neural nets, image coding, image filtering, learning (artificial intelligence), steganography, CNN, ReST-Net, wide structure BibRef

Zou, Y.[Ying], Zhang, G.[Ge], Liu, L.[Leian],
Research on image steganography analysis based on deep learning,
JVCIR(60), 2019, pp. 266-275.
Elsevier DOI 1903
Steganalysis, Steganography, Feature learning, Deep learning, Convolutional neural network, Transfer learning, Multitask learning BibRef

Su, A., Zhao, X.,
Boosting Image Steganalysis Under Universal Deep Learning Architecture Incorporating Ensemble Classification Strategy,
SPLetters(26), No. 12, December 2019, pp. 1852-1856.
IEEE DOI 2001
convolutional neural nets, data compression, image classification, image coding, image fusion, ensemble BibRef

Luo, T.[Ting], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Zhong, C.M.[Cai-Ming], Xu, H.Y.[Hai-Yong], Pan, Z.Y.[Zhi-Yong],
Convolutional neural networks-based stereo image reversible data hiding method,
JVCIR(61), 2019, pp. 61-73.
Elsevier DOI 1906
Convolutional neural network (CNN), Predictor, Prediction error expansion (PEE), Stereo image BibRef

Luo, T.[Ting], Jiang, G.Y.[Gang-Yi], Yu, M.[Mei], Shao, F.[Feng], Peng, Z.J.[Zong-Ju],
Disparity based stereo image reversible data hiding,
ICIP14(5492-5496)
IEEE DOI 1502
Art BibRef

Ye, D.P.[Deng-Pan], Jiang, S.Z.[Shun-Zhi], Li, S.Y.[Shi-Yu], Liu, C.R.[Chang-Rui],
Faster and transferable deep learning steganalysis on GPU,
RealTimeIP(16), No. 3, June 2019, pp. 623-633.
WWW Link. 1906
BibRef

Sun, Y.[Yu], Zhang, H.[Hao], Zhang, T.[Tao], Wang, R.[Ran],
Deep neural networks for efficient steganographic payload location,
RealTimeIP(16), No. 3, June 2019, pp. 635-647.
WWW Link. 1906
BibRef

Ni, D., Feng, G., Shen, L., Zhang, X.,
Selective Ensemble Classification of Image Steganalysis Via Deep Q Network,
SPLetters(26), No. 7, July 2019, pp. 1065-1069.
IEEE DOI 1906
Feature extraction, Training, Signal processing algorithms, Reinforcement learning, Optimization, Deep Q Network BibRef

Liu, J.R.[Jia-Rui], Lu, W.[Wei], Zhan, Y.L.[Yi-Lin], Chen, J.J.[Jun-Jia], Xu, Z.P.[Zhao-Peng], Li, R.P.[Rui-Peng],
Efficient binary image steganalysis based on ensemble neural network of multi-module,
RealTimeIP(17), No. 1, February 2020, pp. 137-147.
Springer DOI 2002
BibRef

Baluja, S.[Shumeet],
Hiding Images within Images,
PAMI(42), No. 7, July 2020, pp. 1685-1697.
IEEE DOI 2006
Containers, Neural networks, Image coding, Image reconstruction, Image color analysis, Training, Receivers, Information hiding, image trust BibRef

Wu, S., Zhong, S., Liu, Y.,
A Novel Convolutional Neural Network for Image Steganalysis With Shared Normalization,
MultMed(22), No. 1, January 2020, pp. 256-270.
IEEE DOI 2001
Training, Feature extraction, Standards, Convolutional neural networks, Task analysis, Data models, shared normalization BibRef

Luo, Y.J.[Yuan-Jing], Qin, J.H.[Jiao-Hua], Xi-Ang, X.[Xuyu], Tan, Y.[Yun], Liu, Q.A.[Qi-Ang], Xiang, L.Y.[Ling-Yun],
Coverless real-time image information hiding based on image block matching and dense convolutional network,
RealTimeIP(17), No. 1, February 2020, pp. 125-135.
Springer DOI 2002
BibRef

Zhou, L., Feng, G., Shen, L., Zhang, X.,
On Security Enhancement of Steganography via Generative Adversarial Image,
SPLetters(27), 2020, pp. 166-170.
IEEE DOI 2002
Steganography, adversarial attacks, GAN, security BibRef

Zhao, D.Y.[Dan-Yang], Wang, K.X.[Kai-Xi],
BNS-CNN: A Blind Network Steganalysis Model Based on Convolutional Neural Network in IPV6 Network,
IWDW19(365-373).
Springer DOI 2003
BibRef

Hung, S.C.[Shi-Chei], Wu, D.C.[Da-Chun], Tsai, W.H.[Wen-Hsiang],
Data Hiding in Computer-Generated Stained Glass Images and Its Applications to Information Protection,
IEICE(E103-D), No. 4, April 2020, pp. 850-865.
WWW Link. 2004
BibRef

Yousfi, Y., Fridrich, J.,
An Intriguing Struggle of CNNs in JPEG Steganalysis and the OneHot Solution,
SPLetters(27), 2020, pp. 830-834.
IEEE DOI 2006
Transform coding, Discrete cosine transforms, Training, Schedules, Detectors, Computer architecture, Convolution, Steganography, deep learning BibRef

Ud Din, S.[Salah], Akhtar, N.[Naveed], Younis, S.[Shahzad], Shafait, F.[Faisal], Mansoor, A.[Atif], Shafique, M.[Muhammad],
Steganographic universal adversarial perturbations,
PRL(135), 2020, pp. 146-152.
Elsevier DOI 2006
Adversarial attack, Steganography, Deep neural networks, Wavelet transform BibRef

Li, L., Zhang, W., Chen, K., Yu, N.,
Steganographic Security Analysis From Side Channel Steganalysis and Its Complementary Attacks,
MultMed(22), No. 10, October 2020, pp. 2526-2536.
IEEE DOI 2009
Social networking (online), Security, Correlation, Image sequences, Distortion, Feature extraction, Digital images, secure region BibRef

Shi, X.Y.[Xiao-Yu], Tondi, B.[Benedetta], Li, B.[Bin], Barni, M.[Mauro],
CNN-based steganalysis and parametric adversarial embedding:A game-theoretic framework,
SP:IC(89), 2020, pp. 115992.
Elsevier DOI 2010
adversarial embedding, Deep learning, Steganography, Steganalysis, Game theory BibRef

Yedroudj, M.[Mehdi], Comby, F.[Frédéric], Chaumont, M.[Marc],
Steganography using a 3-player game,
JVCIR(72), 2020, pp. 102910.
Elsevier DOI 1806
Steganalysis, Deep learning, CNN, GAN BibRef

Ruiz, H.[Hugo], Chaumont, M.[Marc], Yedroudj, M.[Mehdi], Amara, A.O.[Ahmed Oulad], Comby, F.[Frédéric], Subsol, G.[Gérard],
Analysis of the Scalability of a Deep-learning Network for Steganography 'into the Wild',
MMForWild20(439-452).
Springer DOI 2103
BibRef

Kang, S.H.[Sang-Hoon], Park, H.H.[Han-Hoon], Park, J.I.[Jong-Il],
Identification of Multiple Image Steganographic Methods Using Hierarchical ResNets,
IEICE(E104-D), No. 2, February 2021, pp. 350-353.
WWW Link. 2102
BibRef

Ravikumar, K.P., Reddy, H.S.M.[H. S. Manjunatha],
Pixel Prediction-Based Image Steganography Using Crow Search Algorithm-Based Deep Belief Network Approach,
IJIG(21), No. 1 2021, pp. 2150002.
DOI Link 2102
BibRef

Ma, S.[Sai], Zhao, X.F.[Xian-Feng],
Steganalytic feature based adversarial embedding for adaptive JPEG steganography,
JVCIR(76), 2021, pp. 103066.
Elsevier DOI 2104
Steganography, Adversarial embedding, Non-data-driven BibRef

Luo, Y.J.[Yuan-Jing], Qin, J.H.[Jiao-Hua], Xiang, X.[Xuyu], Tan, Y.[Yun],
Coverless Image Steganography Based on Multi-Object Recognition,
CirSysVideo(31), No. 7, July 2021, pp. 2779-2791.
IEEE DOI 2107
Use features of whole image for hiding, easy to attack. Robustness, Feature extraction, Dictionaries, Proposals, Resists, Tools, Indexes, Coverless steganography, object detection, ResNet BibRef

Zhong, N., Qian, Z., Wang, Z., Zhang, X., Li, X.,
Batch Steganography via Generative Network,
CirSysVideo(31), No. 1, January 2021, pp. 88-97.
IEEE DOI 2101
Payloads, Matrix converters, Distortion, Resource management, Convolution, Training, Linear programming, Batch steganography, information hiding BibRef

Li, Y.F.[Ya-Feng], Liu, J.[Ju], Liu, X.X.[Xiao-Xi], Wang, X.J.[Xue-Jing], Gao, X.S.[Xue-Song], Zhang, Y.Y.[Yu-Yi],
HCISNet: Higher-capacity invisible image steganographic network,
IET-IPR(15), No. 13, 2021, pp. 3332-3346.
DOI Link 2110
image watermarking, learning (artificial intelligence), steganography BibRef

Qin, C.[Chuan], Zhang, W.M.[Wei-Ming], Dong, X.Y.[Xiao-Yi], Zha, H.Y.[Hong-Yue], Yu, N.H.[Neng-Hai],
Adversarial steganography based on sparse cover enhancement,
JVCIR(80), 2021, pp. 103325.
Elsevier DOI 2110
Steganography, Adversarial example, Deep neural network BibRef

Peng, F.[Fei], Chen, G.[Guanfu], Long, M.[Min],
A Robust Coverless Steganography Based on Generative Adversarial Networks and Gradient Descent Approximation,
CirSysVideo(32), No. 9, September 2022, pp. 5817-5829.
IEEE DOI 2209
Steganography, Generative adversarial networks, Generators, Data mining, Neural networks, Image segmentation, Distortion, gradient descent BibRef

Weng, S.W.[Shao-Wei], Chen, M.[Mengfei], Yu, L.F.[Li-Fang], Sun, S.Y.[Shi-Yao],
Lightweight and Effective Deep Image Steganalysis Network,
SPLetters(29), 2022, pp. 1888-1892.
IEEE DOI 2209
Convolution, Feature extraction, Signal to noise ratio, Correlation, Standards, Steganography, Training, Deep learning, MGP BibRef

Fu, T.[Tong], Chen, L.Q.[Li-Quan], Fu, Z.J.[Zhang-Jie], Yu, K.[Kunliang], Wang, Y.[Yu],
CCNet: CNN model with channel attention and convolutional pooling mechanism for spatial image steganalysis,
JVCIR(88), 2022, pp. 103633.
Elsevier DOI 2210
Steganalysis, Convolutional neural network, Channel attention, Convolutional pooling BibRef

Liu, J.H.[Jia-Hao], Jiao, G.[Ge], Sun, X.Y.[Xi-Yu],
Feature Passing Learning for Image Steganalysis,
SPLetters(29), 2022, pp. 2233-2237.
IEEE DOI 2212
Feature extraction, Convolution, Steganography, Shape, Deep learning, Training, Task analysis, Image steganalysis, Feature passing, Lightweight BibRef

Jia, J.[Jun], Gao, Z.P.[Zhong-Pai], Chen, K.[Kang], Hu, M.H.[Meng-Han], Min, X.K.[Xiong-Kuo], Zhai, G.T.[Guang-Tao], Yang, X.K.[Xiao-Kang],
RIHOOP: Robust Invisible Hyperlinks in Offline and Online Photographs,
Cyber(52), No. 7, July 2022, pp. 7094-7106.
IEEE DOI 2207
Cameras, Hypertext systems, Decoding, Watermarking, Visualization, Robustness, Training, 3-D rendering, adversarial training, quick response (QR) code BibRef

Qin, X.H.[Xing-Hong], Li, B.[Bin], Tan, S.Q.[Shun-Quan], Tang, W.X.[Wei-Xuan], Huang, J.W.[Ji-Wu],
Gradually Enhanced Adversarial Perturbations on Color Pixel Vectors for Image Steganography,
CirSysVideo(32), No. 8, August 2022, pp. 5110-5123.
IEEE DOI 2208
Costs, Color, Image color analysis, Perturbation methods, Convolutional neural networks, Steganography, Payloads BibRef

Pan, W.W.[Wen-Wen], Yin, Y.L.[Yan-Ling], Wang, X.C.[Xin-Chao], Jing, Y.C.[Yong-Cheng], Song, M.L.[Ming-Li],
Seek-and-Hide: Adversarial Steganography via Deep Reinforcement Learning,
PAMI(44), No. 11, November 2022, pp. 7871-7884.
IEEE DOI 2210
Steganography, Containers, Reinforcement learning, Receivers, Convolutional neural networks, Task analysis, Location awareness, reinforcement learning BibRef

Yang, J.[Junxue], Liao, X.[Xin],
ACGIS: Adversarial Cover Generator for Image Steganography with Noise Residuals Features-Preserving,
SP:IC(113), 2023, pp. 116927.
Elsevier DOI 2303
Steganography, Adversarial cover, Siamese generative network, Sub-regions noise residuals features BibRef

Hu, M.Z.[Ming-Zhi], Wang, H.X.[Hong-Xia],
Image Steganalysis Against Adversarial Steganography by Combining Confidence and Pixel Artifacts,
SPLetters(30), 2023, pp. 987-991.
IEEE DOI 2309
BibRef

Li, W.X.[Wei-Xiang], Wu, S.[Shihang], Li, B.[Bin], Tang, W.X.[Wei-Xuan], Zhang, X.P.[Xin-Peng],
Payload-Independent Direct Cost Learning for Image Steganography,
CirSysVideo(34), No. 3, March 2024, pp. 1970-1975.
IEEE DOI 2403
Costs, Payloads, Training, Security, Probability, Encoding, Image steganography, steganalysis, automatic cost learning, reinforcement learning BibRef

Luo, P.[Peng], Liu, J.[Jia], Xu, J.[Jingting], Dang, Q.[Qian], Mu, D.J.[De-Jun],
Remote Sensing Images Secure Distribution Scheme Based on Deep Information Hiding,
RS(16), No. 8, 2024, pp. 1331.
DOI Link 2405
BibRef

Hu, X.J.[Xin-Jue], Fu, Z.J.[Zhang-Jie], Zhang, X.[Xiang], Chen, Y.[Yanyu],
Invisible and Steganalysis-Resistant Deep Image Hiding Based on One-Way Adversarial Invertible Networks,
CirSysVideo(34), No. 7, July 2024, pp. 6128-6143.
IEEE DOI 2407
Visualization, Steganography, Computational modeling, Couplings, Feature extraction, Task analysis, Distortion, steganalysis BibRef

Zhu, Y.L.[Yu-Ling], Dong, Y.Y.[Yun-Yun], Song, B.B.[Bing-Bing], Yao, S.[Shaowen],
Hiding image into image with hybrid attention mechanism based on GANs,
IET-IPR(18), No. 10, 2024, pp. 2679-2689.
DOI Link 2408
data privacy, data protection, image processing BibRef

Yang, S.C.[Shi-Chen], Jia, X.X.[Xing-Xing], Zou, F.[Fuhua], Zhang, Y.S.J.[Yang-Shi-Jie], Yuan, C.S.[Cheng-Sheng],
A novel hybrid network model for image steganalysis,
JVCIR(103), 2024, pp. 104251.
Elsevier DOI 2409
Image steganalysis, Convolutional neural networks, Bidirectional long short-term memory, Attention mechanism BibRef

Gubri, M.[Martin], Cordy, M.[Maxime], Papadakis, M.[Mike], Le Traon, Y.[Yves], Sen, K.[Koushik],
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity,
ECCV22(IV:603-618).
Springer DOI 2211
BibRef

Ghamizi, S.[Salah], Cordy, M.[Maxime], Papadakis, M.[Mike], Le Traon, Y.[Yves],
Evasion Attack STeganography: Turning Vulnerability Of Machine Learning To Adversarial Attacks Into A Real-world Application,
AROW21(31-40)
IEEE DOI 2112
Steganography, Machine learning algorithms, Image coding, Watermarking, Detectors, Media, Turning BibRef

Lu, S.P.[Shao-Ping], Wang, R.[Rong], Zhong, T.[Tao], Rosin, P.L.[Paul L.],
Large-capacity Image Steganography Based on Invertible Neural Networks,
CVPR21(10811-10820)
IEEE DOI 2111
Backpropagation, Steganography, Visualization, Inverse problems, Neural networks, Computer architecture BibRef

Hu, Y.T.[Yu-Ting], Cao, H.[Han], Yang, Z.L.[Zhong-Liang], Huang, Y.F.[Yong-Feng],
Improving Text-image Matching with Adversarial Learning and Circle Loss for Multi-modal Steganography,
IWDW20(41-52).
Springer DOI 2103
BibRef

Xiao, Y., Wang, C., Gao, X.,
Evade Deep Image Retrieval by Stashing Private Images in the Hash Space,
CVPR20(9648-9657)
IEEE DOI 2008
Privacy, Hamming distance, Image retrieval, Visualization, Perturbation methods, Machine learning BibRef

Wengrowski, E.[Eric], Dana, K.[Kristin],
Light Field Messaging With Deep Photographic Steganography,
CVPR19(1515-1524).
IEEE DOI 2002
BibRef

Zhang, X.P.[Xun-Peng], Kong, X.W.[Xiang-Wei], Wang, P.[Pengda], Wang, B.[Bo],
Cover-source Mismatch in Deep Spatial Steganalysis,
IWDW19(71-83).
Springer DOI 2003
BibRef

Wu, H.B.[Hai-Bin], Li, F.Y.[Feng-Yong], Zhang, X.P.[Xin-Peng], Wu, K.[Kui],
GAN-based Steganography with the Concatenation of Multiple Feature Maps,
IWDW19(3-17).
Springer DOI 2003
BibRef

Xue, Y.M.[Yi-Ming], Peng, W.L.[Wan-Li], Wang, Y.Z.[Yu-Zhu], Wen, J.[Juan], Zhong, P.[Ping],
Optimized CNN with Point-wise Parametric Rectified Linear Unit for Spatial Image Steganalysis,
IWDW19(32-42).
Springer DOI 2003
BibRef

Zhang, J.H.[Jing-Hong], Yi, X.W.[Xiao-Wei], Zhao, X.F.[Xian-Feng], Cao, Y.[Yun],
Light Multiscale Conventional Neural Network for MP3 Steganalysis,
IWDW19(43-56).
Springer DOI 2003
BibRef

Li, Q.J.[Qiang-Jie], Feng, G.R.[Guo-Rui], Wu, H.Z.[Han-Zhou], Zhang, X.P.[Xin-Peng],
Ensemble Steganalysis Based on Deep Residual Network,
IWDW19(84-95).
Springer DOI 2003
BibRef

Zhang, S.Y.[Shi-Yang], Zhang, H.[Hong], Zhao, X.F.[Xian-Feng], Yu, H.B.[Hai-Bo],
A Deep Residual Multi-scale Convolutional Network for Spatial Steganalysis,
IWDW18(40-52).
Springer DOI 1905
BibRef

Lu, Y.Y., Yang, Z.L.O., Zheng, L., Zhang, Y.,
Importance of Truncation Activation in Pre-Processing for Spatial and Jpeg Image Steganalysis,
ICIP19(689-693)
IEEE DOI 1910
image steganalysis, image pre-processing, convolutional neural network, truncation activation BibRef

ur Rehman, A.[Atique], Rahim, R.[Rafia], Nadeem, S.[Shahroz], ul Hussain, S.[Sibt],
End-to-End Trained CNN Encoder-Decoder Networks for Image Steganography,
WiCV-E18(IV:723-729).
Springer DOI 1905
BibRef

Zhang, Q.[Qian], Zhao, X.F.[Xian-Feng], Liu, C.J.[Chang-Jun],
Convolutional Neural Network for Larger JPEG Images Steganalysis,
IWDW18(14-28).
Springer DOI 1905
BibRef

Zha, H., Zhang, W., Qin, C., Yu, N.,
Direct Adversarial Attack on Stego Sandwiched Between Black Boxes,
ICIP19(2284-2288)
IEEE DOI 1910
adversarial attack, steganography, deep learning, steganalysis BibRef

Liu, J.Y.[Jia-Yang], Zhang, W.M.[Wei-Ming], Zhang, Y.W.[Yi-Wei], Hou, D.D.[Dong-Dong], Liu, Y.J.[Yu-Jia], Zha, H.Y.[Hong-Yue], Yu, N.H.[Neng-Hai],
Detection Based Defense Against Adversarial Examples From the Steganalysis Point of View,
CVPR19(4820-4829).
IEEE DOI 2002
BibRef

Zhu, J.[Jiren], Kaplan, R.[Russell], Johnson, J.[Justin], Fei-Fei, L.[Li],
HiDDeN: Hiding Data With Deep Networks,
ECCV18(XV: 682-697).
Springer DOI 1810
BibRef

Yang, J.H.[Jian-Hua], Liu, K.[Kai], Kang, X.G.[Xian-Gui], Wong, E.[Edward], Shi, Y.Q.[Yun-Qing],
Steganalysis Based on Awareness of Selection-Channel and Deep Learning,
IWDW17(263-272).
Springer DOI 1708
BibRef

Liu, K.[Kai], Yang, J.H.[Jian-Hua], Kang, X.G.[Xian-Gui],
Ensemble of CNN and rich model for steganalysis,
WSSIP17(1-5)
IEEE DOI 1707
Complexity theory, Computational modeling, Correlation, Error analysis, Feature extraction, Training, CNN, Ensemble, Rich Model, Steganalysis BibRef

Sharifzadeh, M., Agarwal, C., Aloraini, M., Schonfeld, D.,
Convolutional neural network steganalysis's application to steganography,
VCIP17(1-4)
IEEE DOI 1804
convolution, feedforward neural nets, image coding, statistical analysis, steganography, image steganography, Smoothing methods BibRef

Raval, N., Machanavajjhala, A., Cox, L.P.,
Protecting Visual Secrets Using Adversarial Nets,
PRIV17(1329-1332)
IEEE DOI 1709
Cameras, Feeds, Loss measurement, Machine learning, Privacy, Training, Visualization BibRef

Qian, Y., Dong, J., Wang, W., Tan, T.,
Learning and transferring representations for image steganalysis using convolutional neural network,
ICIP16(2752-2756)
IEEE DOI 1610
Convolution BibRef

Xu, X.Y.[Xiao-Yu], Sun, Y.F.[Yi-Feng], Tang, G.M.[Guang-Ming], Chen, S.Y.[Shi-Yuan], Zhao, J.[Jian],
Deep Learning on Spatial Rich Model for Steganalysis,
IWDW16(564-577).
Springer DOI 1703
BibRef

Chapter on OCR, Document Analysis and Character Recognition Systems continues in
Data Hiding, Steganography, Pixel Difference .