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收稿：2021-06-28，
修回：2021-9-24，
录用：2021-10-1，
纸质出版：2022-01-16
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随着智能设备和社交网络的飞速发展，通过网络传输的数字图像成为了实施隐蔽通信的新型重要载体，适应网络信道的图像隐写技术有望成为开放网络环境下可靠、隐蔽传递信息的一种重要方式。然而，数字图像通过Facebook、Twitter、微信、微博等社交网络传输的过程中，往往会遭受压缩、缩放、滤波等处理，对传统信息隐藏技术在兼顾鲁棒性与抗检测性方面提出了新的挑战。为此，研究者经过多年的努力探索，提出了可抵抗多种图像处理攻击和统计检测的新型鲁棒隐写技术。本文结合网络有损信道中隐蔽通信应用需求，对现有的数字图像鲁棒隐写技术进行综述。首先简要介绍本领域的研究背景，并从图像水印和隐写两方面对图像信息隐藏技术的基本概念、相关技术和发展趋势进行了简要总结。在此基础上，将图像鲁棒隐写技术的研究架构分为载体图像选择、鲁棒载体构造、嵌入代价度量、嵌入通道选择、信源/信道编码以及应用安全策略等方面，并分别对相关方法的基本原理进行了归纳和阐述。随后，对具有代表性的相关方法进行了对比测试，并结合应用场景需求给出了推荐的鲁棒隐写方法。最后，指出了数字图像鲁棒隐写技术有待进一步研究解决的问题。
Cyberspace security is intensively related to national security
national strategy and important policy guidance at present. Information content security is an essential part of cyberspace security. The issue of information prevention in context of illegal theft
tampering and destruction during network transmission has become a key aspect on national security and economic development. Image steganography is one of the hot research directions in the field of information security
which can embed secret message in the redundant part of digital images and transmit through open channels to realize safe and reliable covert communication
and has been widely used in national defense and civilian fields. With the rapid development of smart mobile devices and social network systems
digital images transmitted through open networks have become an important new carrier for covert communication
and the image steganography technology adapted to network channels is expected to become an important way of reliable and covert information transmission in open network environment. However
digital images are often subject to compression
scaling
filtering
etc. during the transmitting through social network systems such as Meta
WeChat and Weibo
and existing information hiding technologies are often difficult to take both the robustness of embedded information and detection resistance of stego images into account. Hence
research on image robust steganography technology that can resist both multiple image processing attacks and statistical detection
and adapt to network lossy channels has important theoretical value and practical significance. After years of hard work
researchers have proposed new robust steganography technologies resisting multiple image processing attacks and statistical detection. Combining with the application requirements of covert communication in network lossy channels
this article reviews the current robust image steganography technologies. First
the related technologies and development trends of image information hiding technology are introduced from two aspects of image watermarking and steganography. For image watermarking technology
the typical robust watermarking algorithms based on image transformation and features are described separately
to discuss the theoretical and technical support that can provide to realize image robust steganography adapted to lossy channels. For image steganography technology
the typical adaptive steganography algorithms are introduced in both spatial and Joint Photographic Experts Group(JPEG) images
to mine the principle and idea of minimizing costs for message embedding. On this basis
the research framework of image robust steganography technology is divided into cover image selection
robust cover construction
embedding cost measurement
embedding channel selection
source/channel coding
and application security policies. Next
the basic principles of related robust steganography methods are summarized and explained from the above six aspects
such as the complexity-based cover image selection algorithm
robust cover construction algorithms based on coefficients relationship
side-information
and image features
embedding cost calculation algorithms utilizing distortion functions
embedding channel selecting algorithms considering image complex and smooth areas
message coding algorithms combining with error-correcting codes and minimizing cost codes
and application security strategy using data decomposition principle. Subsequently
comparative tests are carried out on the representative related methods in terms of robustness against multiple image processing attacks and detection resistance against statistical steganalysis features
and the recommended robust steganography methods are given based on the requirements of the application scenario. For example
if the target transmission channel only contains JPEG compression attacks
according to whether the compression parameters are known
the robust steganography algorithms based on coefficients relationship that resist multiple parameter JPEG compression attacks can be selected
or the robust steganography algorithms based on quantization step size and channel matching that have strong robustness and high reliability against specific parameter compression attacks can be utilized; if the target transmission channel contains multiple image processing attacks with unknown parameters such as compression and scaling
the robust steganography algorithm combined with Reed Solomon (RS) error correction coding that has strong error correction capability can be selected according to the requirements for communication reliability
or the robust steganography algorithm with strong error detection capability and combined with cyclic redundancy check (CRC) detection/error correction coding can be utilized for reliable covert communication. At last
some problems to be solved in the field of image robust steganography techniques are pointed out
in terms of accurate characterization of the influence of network lossy channels on stego sequence
virtual cover construction with multiple robustness and invisibility and so on. In general
the demand for covert communication in network lossy channels has brought new opportunities and challenges to image steganography
which contains many problems worthy of further research and exploration. Researchers need to make continuous efforts and gradually advance the process of image steganography from the laboratory to real life.
Ansari I A and Pant M. 2017. Multipurpose image watermarking in the domain of DWT based on SVD and ABC. Pattern Recognition Letters, 94: 228-236 [DOI: 10.1016/j.patrec.2016.12.010]
Bao Z K, Guo Y Q, Li X L, Zhang Y, Xu M and Luo X Y. 2020. A robust image steganography based on the concatenated error correction encoder and discrete cosine transform coefficients. Journal of Ambient Intelligence and Humanized Computing, 11(5): 1889-1901 [DOI: 10.1007/s12652-019-01345-8]
Chang C C, Lin C C and Su G D. 2020. An effective image self-recovery based fragile watermarking using self-adaptive weight-based compressed AMBTC. Multimedia Tools and Applications, 79(33): 24795-24824 [DOI: 10.1007/s11042-020-09132-w]
Cheddad A, Condell J, Curran K and Mc Kevitt M. 2010. Digital image steganography: survey and analysis of current methods. Signal Processing, 90(3): 727-752 [DOI: 10.1016/j.sigpro.2009.08.010]
Chen D Y, Ouhyoung M and Wu J L. 2000. A shift-resisting public watermark system for protecting image processing software. IEEE Transactions on Consumer Electronics, 46(3): 404-414 [DOI: 10.1109/30.883385]
Chen K J. 2020. Research on Steganographic Security Enhancement and Distribution Preserving Steganography. Hefei: University of Science and Technology of China
陈可江. 2020. 隐写安全性增强与分布保持隐写研究. 合肥: 中国科学技术大学
Chen K J, Zhang W M, Zhou H, Yu N H and Feng G R. 2016. Defining cost functions for adaptive steganography at the microscale//Proceedings of the 2016 IEEE International Workshop on Information Forensics and Security. Abu Dhabi, United Arab Emirates: IEEE: 1-6 [ DOI: 10.1109/WIFS.2016.7823900 http://dx.doi.org/10.1109/WIFS.2016.7823900 ]
Chen M Q, Niu X X and Yang Y X. 2001. The research developments and applications of digital watermarking. Journal of China Institute of Communications, 22(5): 71-79
陈明奇, 钮心忻, 杨义先. 2001. 数字水印的研究进展和应用. 通信学报, 22(5): 71-79) [DOI: 10.3321/j.issn:1000-436X.2001.05.013]
Chen Y, Li Z, Zhang J and Wang G M. 2019. Robust watermarking algorithm for diffusion weighted images. Journal of Image and Graphics, 24(9): 1434-1449
陈怡, 李智, 张健, 王国美. 2019. 弥散加权图像的鲁棒水印算法研究. 中国图象图形学报, 24(9): 1434-1449) [DOI: 10.11834/jig.180672]
Cox I. 2002. Digital watermarking. Journal of Electronic Imaging, 2002, 11(3): #414 [ DOI: 10.1117/1.1494075 http://dx.doi.org/10.1117/1.1494075 ]
Denemark T and Fridrich J. 2015. Improving steganographic security by synchronizing the selection channel//Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia Security. Portland, USA: ACM: 5-14 [ DOI: 10.1145/2756601.2756620 http://dx.doi.org/10.1145/2756601.2756620 ]
Denemark T and Fridrich J. 2017. Model based steganography with precover. Electronic Imaging, 2017(7): 56-66 [DOI: 10.2352/ISSN.2470-1173.2017.7.MWSF-326]
Ebel W J and Tranter W H. 1995. The performance of Reed-Solomon codes on a bursty-noise channel. IEEE Transactions on Communications, 43(2/4): 298-306 [DOI: 10.1109/26.380048]
Fang H, Zhang W M, Zhou H, Cui H and Yu N H. 2019. Screen-shooting resilient watermarking. IEEE Transactions on Information Forensics and Security, 14(6): 1403-1418 [DOI: 10.1109/TIFS.2018.2878541]
Filler T and Fridrich J. 2011. Design of adaptive steganographic schemes for digital images//Proceedings Volume 7880, Media Watermarking, Security, and Forensics Ⅲ. San Francisco, USA: SPIE: #78800F [ DOI: 10.1117/12.872192 http://dx.doi.org/10.1117/12.872192 ]
Filler T, Judas J and Fridrich J. 2010. Minimizing embedding impact in steganography using trellis-coded quantization//Proceedings Volume 7541, Media Forensics and Security Ⅱ. San Jose, USA: SPIE: 754105: 1-14 [ DOI: doi.org/10.1117/12.838002 http://dx.doi.org/doi.org/10.1117/12.838002 ]
Fridrich J. 2009. Steganography in Digital Media: Principles, Algorithms, and Applications. Cambridge: Cambridge University Press
Fridrich J, Goljan M and Soukal D. 2004. Perturbed quantization steganography with wet paper codes//Proceedings of 2004 Workshop on Multimedia and Security. Magdeburg, Germany: ACM: 4-15 [ DOI: 10.1145/1022431.1022435 http://dx.doi.org/10.1145/1022431.1022435 ]
Fridrich J and Kodovsky J. 2012. Rich models for steganalysis of digital images. IEEE Transactions on Information Forensics and Security, 7(3): 868-882 [DOI: 10.1109/TIFS.2012.2190402]
Fridrich J, PevnýT and KodovskýJ. 2007. Statistically undetectable JPEG steganography: dead ends challenges, and opportunities//Proceedings of the 9th Workshop on Multimedia and Security. Dallas, USA: ACM: 3-14 [ DOI: 10.1145/1288869.1288872 http://dx.doi.org/10.1145/1288869.1288872 ]
Guo L J, Ni J Q and Shi Y Q. 2012. An efficient JPEG steganographic scheme using uniform embedding//Proceedings of the 2012 IEEE International Workshop on Information Forensics and Security. Costa Adeje, Spain: IEEE: 169-174 [ DOI: 10.1109/WIFS.2012.6412644 http://dx.doi.org/10.1109/WIFS.2012.6412644 ]
He H J, Chen F, Tai H M, Kalker T and Zhang J S. 2012. Performance analysis of a block-neighborhood-based self-recovery fragile watermarking scheme. IEEE Transactions on Information Forensics and Security, 7(1): 185-196 [DOI: 10.1109/TIFS.2011.2162950]
Holotyak T, Fridrich J and Soukal D. 2005. Stochastic approach to secret message length estimation in ±K embedding steganography//Proceedings Volume 5681, Security, Steganography, and Watermarking of Multimedia Contents Ⅶ. San Jose, USA: SPIE: 673-684 [ DOI: 10.1117/12.584201 http://dx.doi.org/10.1117/12.584201 ]
Holub V and Fridrich J. 2012. Designing steganographic distortion using directional filters//Proceedings of 2012 IEEE International Workshop on Information Forensics and Security. Costa Adeje, Spain: IEEE: 234-239 [ DOI: 10.1109/WIFS.2012.6412655 http://dx.doi.org/10.1109/WIFS.2012.6412655 ]
Holub V and Fridrich J. 2013. Digital image steganography using universal distortion//Proceedings of the 1 st ACM Workshop on Information Hiding and Multimedia Security. Montpellier, France: ACM: 59-68 [ DOI: 10.1145/2482513.2482514 http://dx.doi.org/10.1145/2482513.2482514 ]
Holub V and Fridrich J. 2015. Low-complexity features for JPEG steganalysis using undecimated DCT. IEEE Transactions on Information Forensics and Security, 10(2): 219-228 [DOI: 10.1109/TIFS.2014.2364918]
Hou X and Min L Q. 2017. A robust watermarking algorithm using SURF feature regions. Geomatics and Information Science of Wuhan University, 42(3): 421-426
侯翔, 闵连权. 2017. 基于SURF特征区域的鲁棒水印算法. 武汉大学学报(信息科学版), 42(3): 421-426) [DOI: 10.13203/j.whugis20140508]
Huang F J, Huang J W and Shi Y Q. 2012. New channel selection rule for JPEG steganography. IEEE Transactions on Information Forensics and Security, 7(4): 1181-1191 [DOI: 10.1109/TIFS.2012.2198213]
Huynh-The T, Hua C H, Tu N A, Hur T, Bang J, Kim D, Amin M B, Kang B H, Seung H and Lee S. 2018. Selective bit embedding scheme for robust blind color image watermarking. Information Sciences, 426: 1-18 [DOI: 10.1016/j.ins.2017.10.016]
Jiang N and Wang J. 2010. Information Theory and Coding Theory. Beijing: Tsinghua University Press
姜楠, 王健. 2010. 信息论与编码理论. 北京: 清华大学出版社
Kandi H, Mishra D and Gorthi S R K S. 2017. Exploring the learning capabilities of convolutional neural networks for robust image watermarking. Computers and Security, 65: 247-268 [DOI: 10.1016/j.cose.2016.11.016]
Ko H J, Huang C T, Horng G and Wang S J. 2020. Robust and blind image watermarking in DCT domain using inter-block coefficient correlation. Information Sciences, 517: 128-147 [DOI: 10.1016/j.ins.2019.11.005]
Koch E and Zhao J. 1995. Towards robust and hidden image copyright labeling//Proceedings of 1995 IEEE Workshop on Nonlinear Signal and Image Processing. Neos Marmaras, Greece: IEEE: 452-455
Kodovsky J, Fridrich J and Holub V. 2011. On dangers of overtraining steganography to incomplete cover model//Proceedings of the 13th ACM Multimedia Workshop on Multimedia and Security. New York, USA: ACM: 69-76 [ DOI: 10.1145/2037252.2037266 http://dx.doi.org/10.1145/2037252.2037266 ]
Koopman P and Chakravarty T. 2004. Cyclic redundancy code (CRC) polynomial selection for embedded networks//Proceedings of the International Conference on Dependable Systems and Networks. Florence, Italy: IEEE: 145-154 [ DOI: 10.1109/DSN.2004.1311885 http://dx.doi.org/10.1109/DSN.2004.1311885 ]
Lagzian S, Soryani M and Fathy M. 2011. A new robust watermarking scheme based on RDWT-SVD. International Journal of Intelligent Information Processing, 2(1): 131-140
Laishram D and Tuithung T. 2021. A novel minimal distortion-based edge adaptive image steganography scheme using local complexity. Multimedia Tools and Applications, 80(1): 831-854 [DOI: 10.1007/s11042-020-09519-9]
Li B, Tan S Q, Wang M and Huang J W. 2014a. Investigation on cost assignment in spatial image steganography. IEEE Transactions on Information Forensics and Security, 9(8): 1264-1277 [DOI: 10.1109/TIFS.2014.2326954]
Li B, Wang M, Huang J W and Li X L. 2014b. A new cost function for spatial image steganography//Proceeding of 2014 IEEE International Conference on Image Processing. Paris, France: IEEE: 4206-4210 [ DOI: 10.1109/ICIP.2014.7025854 http://dx.doi.org/10.1109/ICIP.2014.7025854 ]
Li B, Wang M, Li X L, Tan S Q and Huang J W. 2015a. A strategy of clustering modification directions in spatial image steganography. IEEE Transactions on Information Forensics and Security, 10(9): 1905-1917 [DOI: 10.1109/TIFS.2015.2434600]
Li C L, Zhang Z X, Wang Y H, Ma B and Huang D. 2015b. Dither modulation of significant amplitude difference for wavelet based robust watermarking. Neurocomputing, 166: 404-415 [DOI: 10.1016/j.neucom.2015.03.039]
Li F Y, Wu K, Qin C and Lei J S. 2020d. Anti-compression JPEG steganography over repetitive compression networks. Signal Processing, 170: #107454 [DOI: 10.1016/j.sigpro.2020.107454]
Li F Y, Wu K, Zhang X P, Yu J, Lei J S and Wen M. 2018. Robust batch steganography in social networks with non-uniform payload and data decomposition. IEEE Access, 6: 29912-29925 [DOI: 10.1109/ACCESS.2018.2841415]
Li W X, Chen K J, Zhang W M, Zhou H, Wang Y F and Yu N H. 2020a. JPEG steganography with estimated side-information. IEEE Transactions on Circuits and Systems for Video Technology, 30(7): 2288-2294 [DOI: 10.1109/TCSVT.2019.2925118]
Li W X, Zhang W M, Li L, Zhou H and Yu N H. 2020b. Designing near-optimal steganographic codes in practice based on polar codes. IEEE Transactions on Communications, 68(7): 3948-3962 [DOI: 10.1109/TCOMM.2020.2982624]
Li W X, Zhou W B, Zhang W M, Qin C, Hu H H and Yu N H. 2020c. Shortening the cover for fast JPEG steganography. IEEE Transactions on Circuits and Systems for Video Technology, 30(6): 1745-1757 [DOI: 10.1109/TCSVT.2019.2908689]
Li Y M, Wei D Y and Zhang L N. 2021a. Double-encrypted watermarking algorithm based on cosine transform and fractional Fourier transform in invariant wavelet domain. Information Sciences, 551: 205-227 [DOI: 10.1016/j.ins.2020.11.020]
Li Z H, ZhangM Q and Liu J. 2021b. Robust image steganography framework based on generative adversarial network. Journal of Electronic Imaging, 30(2): #023006 [DOI: 10.1117/1.JEI.30.2.023006]
Liao X, Yin J J, Chen M L and Qin Z. 2021. Adaptive payload distribution in multiple images steganography based on image texture features. IEEE Transactions on Dependable and Secure Computing [DOI: 10.1109/TDSC.2020.3004708]
Lu W, Lu H T and Chung F L. 2010. Feature based robust watermarking using image normalization. Computers and Electrical Engineering, 36(1): 2-18 [DOI: 10.1016/j.compeleceng.2009.04.002]
Lu W, Zhang J H, Zhao X F, Zhang W M and Huang J W. 2021. Secure robust JPEG steganography based on autoencoder with adaptive BCH encoding. IEEE Transactions on Circuits and Systems for Video Technology, 31(7): 2909-2922 [DOI: 10.1109/TCSVT.2020.3027843]
Luo W B, Heileman G L and Pizano C E. 2002. Fast and robust watermarking of JPEG files//The 5th IEEE Southwest Symposium on Image Analysis and Interpretation. Sante Fe, USA: IEEE: 158-162 [ DOI: 10.1109/IAI.2002.999910 http://dx.doi.org/10.1109/IAI.2002.999910 ]
Luo W Q, Huang F J and Huang J W. 2010. Edge adaptive image steganography based on LSB matching revisited. IEEE Transactions on Information Forensics and Security, 5(2): 201-214 [DOI: 10.1109/TIFS.2010.2041812]
Ma B, Chang L L, Wang C P, Li J, Wang X Y and Shi Y Q. 2020. Robust image watermarking using invariant accurate polar harmonic Fourier moments and chaotic mapping. Signal Processing, 172: #107544 [DOI: 10.1016/j.sigpro.2020.107544]
Maity S P, Maity S, Sil J and Delpha C. 2013. Collusion resilient spread spectrum watermarking in M-band wavelets using GA-fuzzy hybridization. Journal of Systems and Software, 86(1): 47-59 [DOI: 10.1016/j.jss.2012.06.057]
Makbol N M and Khoo B E. 2014. A new robust and secure digital image watermarking scheme based on the integer wavelet transform and singular value decomposition. Digital Signal Processing, 33: 134-147 [DOI: 10.1016/j.dsp.2014.06.012]
Papakostas G A, Koulouriotis D. E and Tourassis V. D. 2012. Performance evaluation of moment-based watermarking methods: a review. Journal of Systems and Software, 85(8): 1864-1884 [DOI: 10.1016/j.jss.2012.02.045]
Pei Y, Luo X Y, Zhang Y and Zhu L Y. 2020. Multiple images steganography of JPEG images based on optimal payload distribution. Computer Modeling in Engineering and Sciences, 125(1): 417-436 [DOI: 10.32604/cmes.2020.010636]
Petitcolas F A P, Anderson R J and Kuhn M G. 1999. Information hiding-a survey. Proceedings of the IEEE, 87(7): 1062-1078 [DOI: 10.1109/5.771065]
Pevný T, Bas P and Fridrich J. 2010a. Steganalysis by subtractive pixel adjacency matrix. IEEE Transactions on Information Forensics and Security, 5(2): 215-224 [DOI: 10.1109/TIFS.2010.2045842]
PevnýT, Filler T and Bas P. 2010b. Using high-dimensional image models to perform highly undetectable steganography//Proceedings of the 12th International Workshop on Information Hiding. Calgary, Canada: ACM: 161-177 [ DOI: 10.1007/978-3-642-16435-4_13 http://dx.doi.org/10.1007/978-3-642-16435-4_13 ]
Pevný T and Fridrich J. 2008. Multiclass detector of current steganographic methods for JPEG format. IEEE Transactions on Information Forensics and Security, 3(4): 635-650 [DOI: 10.1109/TIFS.2008.2002936]
Provos N. 2001. Outguess-universal steganography[EB/OL]. [2021-06-28] . http://www.Outguess.-org/ http://www.Outguess.-org/
Qiao T, Wang S, Luo X Y and Zhu Z Q. 2021. Robust steganography resisting JPEG compression by improving selection of cover element. Signal Processing, 183: #108048 [DOI: 10.1016/j.sigpro.2021.108048]
Sallee P. 2003. Model-based steganography//Proceedings of the 2nd International Workshop on Digital Watermarking. Seoul, Korea(South): Springer: 154-167 [ DOI: 10.1007/978-3-540-24624-4_12 http://dx.doi.org/10.1007/978-3-540-24624-4_12 ]
Sallee P. 2005. Model-based methods for steganography and steganalysis. International Journal of Image and Graphics, 5(1): 167-189 [DOI: 10.1142/S0219467805001719]
Sedighi V, Cogranne R and Fridrich J. 2016. Content-adaptive steganography by minimizing statistical detectability. IEEE Transactions on Information Forensics and Security, 11(2): 221-234 [DOI:10.1109/TIFS.2015.2486744]
Shen C X, Zhang H G, Feng D G, Cao Z F and Huang J W. 2007. Information security overview. Science China E: Information Sciences, 37(2): 129-150
沈昌祥, 张焕国, 冯登国, 曹珍富, 黄继武. 2007. 信息安全综述. 中国科学E辑: 信息科学, 37(2): 129-150
Su A T, Ma S and Zhao X F. 2020. Fast and secure steganography based on J-UNIWARD. IEEE Signal Processing Letters, 27: 221-225 [DOI: 10.1109/LSP.2020.2964485]
Su W K, Ni J Q, Hu X L and Fridrich J. 2021. Image steganography with symmetric embedding using Gaussian Markov random field model. IEEE Transactions on Circuits and Systems for Video Technology, 31(3): 1001-1015 [DOI: 10.1109/TCSVT.2020.3001122]
Subramanyam A V, Emmanuel S and Kankanhalli M S. 2012. Robust watermarking of compressed and encrypted JPEG2000 images. IEEE Transactions on Multimedia, 14(3): 703-716 [DOI: 10.1109/TMM.2011.2181342]
Sun K. 2020. An image remake detection method based on LBP watermark features and fine-grained recognition. China, 202010628464.2
孙鲲. 2020. 一种基于LBP水印特征和细粒度识别的图像翻拍检测方法. 中国, 202010628464.2
Sun S H. 2004. Digital Watermarking Technology and Application. Beijing: Science Press
孙圣和. 2004. 数字水印技术及应用. 北京: 科学出版社
Tan S Q. 2007. Research on JPEG2000 Image Steganalysis. Guangzhou: Sun Yat-sen University
谭舜泉. 2007. 基于JPEG2000的图像隐写分析研究. 广州: 中山大学
Tang W X, Li B, Tan S Q, Barni M and Huang J W. 2019. CNN-based adversarial embedding for image steganography. IEEE Transactions on Information Forensics and Security, 14(8): 2074-2087 [DOI: 10.1109/TIFS.2019.2891237]
Tao J Y, Li S, Zhang X P and Wang Z C. 2019. Towards robust image steganography. IEEE Transactions on Circuits and Systems for Video Technology, 29(2): 594-600 [DOI: 10.1109/TCSVT.2018.2881118]
Tong X J, Liu Y, Zhang M and Chen Y. 2013. A novel chaos-based fragile watermarking for image tampering detection and self-recovery. Signal Processing: Image Communication, 28(3): 301-308 [DOI: 10.1016/j.image.2012.12.003]
Tsai J S, Huang W B and Kuo Y H. 2011. On the selection of optimal feature region set for robust digital image watermarking. IEEE Transactions on Image Processing, 20(3): 735-743 [DOI: 10.1109/TIP.2010.2073475]
Tsai J S, Huang W B, Kuo Y H and Horng M F. 2012. Joint robustness and security enhancement for feature-based image watermarking using invariant feature regions. Signal Processing, 92(6): 1431-1445 [DOI: 10.1016/j.sigpro.2011.11.033]
Tsougenis E D, Papakostas G A, Koulouriotis D E and Tourassis V D. 2012. Performance evaluation of moment-based watermarking methods: a review. Journal of Systems and Software, 85(8): 1864-1884 [DOI: 10.1016/j.jss.2012.02.045]
Upham D. 2021. JPEG-Jsteg-V4[EB/OL]. [2021-05-22] . http://www.funet.fi/pub/crypt/steganography/jpeg-JSteg-v4.diff.gz http://www.funet.fi/pub/crypt/steganography/jpeg-JSteg-v4.diff.gz
Valizadeh A and Wang Z J. 2012. An improved multiplicative spread spectrum embedding scheme for data hiding. IEEE Transactions on Information Forensics and Security, 7(4): 1127-1143 [DOI: 10.1109/TIFS.2012.2199312]
Wang C T, Ni J Q, Huang J W and Zhang R Y. 2008. A RST-invariant robust DWT-HMM watermarking algorithm incorporating Zernike moment and template. Journal of Image and Graphics, 13(7): 1250-1257
王春桃, 倪江群, 黄继武, 张荣跃. 2008. 结合Zernike矩和模板具有RST不变性的DWT-HMM鲁棒水印算法. 中国图象图形学报, 13(7): 1250-1257) [DOI: 10.11834/jig.20080705]
Wang C T, Ni J Q, Zhuo H S and Huang J W. 2011. A geometrically invariant robust image watermarking based on deformable multi-scale transform. Acta Automatica Sinica, 37(11): 1368-1380
王春桃, 倪江群, 卓华硕, 黄继武. 2011. 基于可变形多尺度变换的几何不变鲁棒图像水印算法. 自动化学报, 37(11): 1368-1380) [DOI: 10.3724/SP.J.1004.2011.01368]
Wang X Y, Niu P P, Yang H Y, Wang C P and Wang A L. 2014. A new robust color image watermarking using local quaternion exponent moments. Information Sciences, 277: 731-754 [DOI: 10.1016/j.ins.2014.02.158]
Wang Y F, Li W X, Zhang W M, Yu X Z, Liu K L and Yu N H. 2021. BBC++: enhanced block boundary continuity on defining non-additive distortion for JPEG steganography. IEEE Transactions on Circuits and Systems for Video Technology, 31(5): 2082-2088 [DOI: 10.1109/TCSVT.2020.3010554]
Westfeld A. 2001. F5-A steganographic algorithm//Proceedings of the 4th International Workshop on Information Hiding. Pittsburgh, USA: Springer: 289-302 [ DOI: 10.1007/3-540-45496-9_21 http://dx.doi.org/10.1007/3-540-45496-9_21 ]
Wu J Q, Zhai L M, Wang L N, Fang C M and Wu T. 2020. Enhancing spatial steganographic algorithm based on multi-scale filters. Journal of Computer Research and Development, 57(11): 2251-2259
吴俊锜, 翟黎明, 王丽娜, 方灿铭, 吴畑. 2020. 基于多尺度滤波器的空域图像隐写增强算法. 计算机研究与发展, 57(11): 2251-2259) [DOI: 10.7544/issn1000-1239.2020.20200441]
Wu K C and Wang C M. 2015. Steganography using reversible texture synthesis. IEEE Transactions on Image Processing, 24(1): 130-139 [DOI: 10.1109/TIP.2014.2371246]
You W K, Zhang H and Zhao X F. 2021. A Siamese CNN for image steganalysis. IEEE Transactions on Information Forensics and Security, 16: 291-306 [DOI: 10.1109/TIFS.2020.3013204]
Yu X Z, Chen K J, Wang Y F, Li W X, Zhang W M and Yu N H. 2020. Robust adaptive steganography based on generalized dither modulation and expanded embedding domain. Signal Processing, 168: #107343 [DOI: 10.1016/j.sigpro.2019.107343]
Zhang X P, Wang S Z, Qian Z X and Feng G R. 2010. Reversible fragile watermarking for locating tampered blocks in JPEG images. Signal Processing, 90(12): 3026-3036 [DOI: 10.1016/j.sigpro.2010.04.027]
Zhang Y, Luo X Y, Guo Y Q, Qin C and Liu F L. 2019. Zernike moment-based spatial image steganography resisting scaling attack and statistic detection. IEEE Access, 7: 24282-24289 [DOI: 10.1109/ACCESS.2019.2900286]
Zhang Y, Luo X Y, Guo Y Q, Qin C and Liu F L. 2020a. Multiple robustness enhancements for image adaptive steganography in lossy channels. IEEE Transactions on Circuits and Systems for Video Technology, 30(8): 2750-2764 [DOI: 10.1109/TCSVT.2019.2923980]
Zhang Y, Luo X Y, Wang J W, Guo Y Q and Liu F L. 2021. Image robust adaptive steganography adapted to lossy channels in open social networks. Information Sciences, 564: 306-326 [DOI: 10.1016/j.ins.2021.02.058]
Zhang Y, Luo X Y, Wang J W, Yang C F and Liu F L. 2018b. A robust image steganography method resistant to scaling and detection. Journal of Internet Technology, 19(2): 607-618 [DOI: 10.3966/160792642018031902029]
Zhang Y, Luo X Y, Yang C F and Liu F L. 2017. Joint JPEG compression and detection resistant performance enhancement for adaptive steganography using feature regions selection. Multimedia Tools and Applications, 76(3): 3649-3668 [DOI: 10.1007/s11042-016-3914-0]
Zhang Y, Luo X Y, Yang C F, Ye D P and Liu F L. 2015. A JPEG-compression resistant adaptive steganography based on relative relationship between DCT coefficients//Proceedings of the 10th International Conference on Availability, Reliability and Security. Toulouse, France: IEEE: 461-466 [ DOI: 10.1109/ARES.2015.53 http://dx.doi.org/10.1109/ARES.2015.53 ]
Zhang Y, Luo X Y, Yang C F, Ye D P and Liu F L. 2016. A framework of adaptive steganography resisting JPEG compression and detection. Security and Communication Networks, 9(15): 2957-2971 [DOI: 10.1002/sec.1502]
Zhang Y, Luo X Y, Zhu X D, Li Z Y and Bors A G. 2020b. Enhancing reliability and efficiency for real-time robust adaptive steganography using cyclic redundancy check codes. Journal of Real-Time Image Processing, 17(1): 115-123 [DOI: 10.1007/s11554-019-00905-7]
Zhang Y, Qin C, Zhang W M, Liu F L and Luo X Y. 2018a. On the fault-tolerant performance for a class of robust image steganography. Signal Processing, 146: 99-111 [DOI: 10.1016/j.sigpro.2018.01.011]
Zhang Y, Ye D P, Gan J J, Li Z Y and Cheng Q F. 2018c. An image steganography algorithm based on quantization index modulation resisting scaling attacks and statistical detection. Computer, Materials and Continua, 56(1): 151-167 [DOI: 10.3970/cmc.2018.02464]
Zhang Y, Zhu X D, Qin C, Yang C F and Luo X Y. 2018d. Dither modulation based adaptive steganography resisting JPEG compression and statistic detection. Multimedia Tools and Applications, 77(14): 17913-17935 [DOI: 10.1007/s11042-017-4506-3]
Zhang Y W, Zhang W M, Chen K J, Liu J Y, Liu Y J and Yu N H. 2018a. Adversarial examples against deep neural network based steganalysis//Proceedings of the 6th ACM Workshop on Information Hiding and Multimedia Security. Innsbruck, Austria: ACM: 67-72 [ DOI: 10.1145/3206004.3206012 http://dx.doi.org/10.1145/3206004.3206012 ]
Zhao N S. 2018. Research on Coverless Information Hiding based on Partial-Duplicate Image Retrieval. Tianjin: Tianjin University
赵宁生. 2018. 基于近重复图像的无载体信息隐藏研究. 天津: 天津大学
Zhao X F and Zhang H. 2018. Principles and Technologies of Steganography. Beijing: Science Press
赵险峰, 张弘. 2018. 隐写学原理与技术. 北京: 科学出版社
Zhao Z Z, Guan Q X, Zhang H and Zhao X F. 2019. Improving the robustness of adaptive steganographic algorithms based on transport channel matching. IEEE Transactions on Information Forensics and Security, 14(7): 1843-1856 [DOI: 10.1109/TIFS.2018.2885438]
Zhou J J and Cai Y. 2008. Network and Information Security Fundamentals. Beijing: Tsinghua University Press
周继军, 蔡毅. 2008. 网络与信息安全基础. 北京: 清华大学出版社
Zhou L, Zhang T Q, Feng J X and Xu W. 2020. Image watermarking algorithm based on Blob-Harris feature region and CT-SVD. Journal of Signal Processing, 36(4): 520-530
周琳, 张天骐, 冯嘉欣, 徐伟. 2020. Blob-Harris特征区域结合CT-SVD的鲁棒图像水印算法. 信号处理, 36(4): 520-530) [DOI: 10.16798/j.issn.1003-0530.2020.04.006]
Zhou W B, Zhang W M and Yu N H. 2017. A new rule for cost reassignment in adaptive steganography. IEEE Transactions on Information Forensics and Security, 12(11): 2654-2667 [DOI: 10.1109/TIFS.2017.2718480]
Zhu L. 2011. Research on Digital Watermarking Technique in Notes and Packaging Anti-Forge. Wuhan: Huazhong University of Science and Technology
祝霖. 2011. 应用于票据与包装防伪的数字水印技术研究. 武汉: 华中科技大学
Zhu L Y, Luo X Y, Yang C F, Zhang Y and Liu F L. 2021a. Invariances of JPEG-quantized DCT coefficients and their application in robust image steganography. Signal Processing, 183: #108015 [DOI: 10.1016/j.sigpro.2021.108015]
Zhu L Y, Luo X Y, Zhang Y, Yang C F and Liu F L. 2021b. Inverse interpolation and its application in robust image steganography. IEEE Transactions on Circuits and Systems for Video Technology: #9521502 [DOI: 10.1109/TCSVT.2021.3107342]
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