A deep learning-driven multi-layered steganographic approach for enhanced data security by Yousef Sanjalawe, Salam Al-E’mari, Salam Fraihat, Mosleh Abualhaj, Emran Alzubi

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Online universal steganalysis system based on multiple pre-trained model by Ya-fei YUAN, Wei LU, Bing-wen FENG, Jian WENG

Subjects: “…digital image steganography…”
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Review of information hiding on Chinese text by Guohua WU, Lichun GONG, Lifeng YUAN, Ye YAO

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Generative blockchain-based covert communication model based on Markov chain by Wei SHE, Xinpeng RONG, Wei LIU, Zhao TIAN

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A STEGENOGRAPHY IN 3D MESH BY REARRANGING THE ORDER OF VERTEX PRESENTATION by Thái Duy Quý

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Cryptographic secrecy of steganographic matrix encoding by Jia-yong CHEN, Jiu-fen LIU, Yue-fei ZHU, Wei-ming ZHANG

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Crayfish optimization based pixel selection using block scrambling based encryption for secure cloud computing environment by Vikas K. Soman, V. Natarajan

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Subtractive pixel adjacency matrix based features for steganalysis of spatial color images by Tao HAN, Xi CHEN, Yue-fei ZHU

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Model of Reconfigurable Steganographic System Using Blockchain Technology by E. V. Timoschenko, A. F. Razhkov

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Film and Television Animation Sensing and Visual Image by Computer Digital Image Technology by Lu Lian, Tong Lei

“…The established image enhancement algorithm can significantly improve the security of the existing spatial image steganography algorithm under different embedding rates, especially at a high embedding rate; the improvement of the spatial domain steganography algorithm is greater. …”
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RETRACTED: Parallel Encryption With Digit Arithmetic Of Covertext Model Using Duplicated Covertext by Hari Murti, Edy Supriyanto, Rara Redjeki, Eka Ardhianto

“…Steganography is the art and science of writing hidden messages or hiding messages in such a way that, apart from the sender and the recipient, no one knows or is aware that there is a secret message (it does not appear that there is a hidden message. …”
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Analisis Pengaruh Citra Terhadap Kombinasi Kriptografi RSA dan STEGANOGRAFi LSB by Agus Rakhmadi Mido, Erik Iman Heri Ujianto

“…Cryptography and steganography have similarities in terms of security. …”
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An Image Sharing Encryption Management System For Kabale University. by Bemera, Rauben

“…Myriad methods of protection are used ranging from a simple authentication password to most complex cryptography or Steganography algorithms for hiding the extremely sensitive data. …”
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Pengamanan Citra Berwarna Menggunakan Kriptografi Visual Skema Meaningful Shares dan Steganografi LSB by Fariz Abid Darmawan, Ari Kusyanti, Rakhmadhanny Primananda

“…To add security, we need Steganography LSB, we can insert the image shares again into the new cover so that the quality and security will increase. …”
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Steganographer identification of JPEG image based on feature selection and graph convolutional representation by Qianqian ZHANG, Yi ZHANG, Hao LI, Yuanyuan MA, Xiangyang LUO

“…Aiming at the problem that the feature dimension of JPEG image steganalysis is too high, which leads to the complexity of distance calculation between users and a decrease in the identification performance of the steganographer, a method for steganographer recognition based on feature selection and graph convolutional representation was proposed.Firstly, the steganalysis features of the user’s images were extracted, and the feature subset with highseparability was selected.Then, the users were represented as a graph, and the features of users were obtained by training the graph convolutional neural network.Finally, because inter-class separability and intra-class aggregation were considered, the features of users that could capture the differences between users were learned.For steganographers who use JPEG steganography, such as nsF5, UED, J-UNIWARD, and so on, to embed secret information in images, the proposed method can reduce the feature dimensions and computing.The identification accuracy of various payloads can reach more than 80.4%, and it has an obvious advantage at the low payload.…”
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Reversible Data Hiding Using Two Marked Images Based on Adaptive Coefficient-Shifting Algorithm by Ching-Yu Yang

“…Furthermore, the number of shadows required by the proposed method is less than that required by the approaches which are based upon secret image sharing with reversible steganography.…”
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Integration of a Quantum Voting Scheme into Grayscale Images Using the Novel Enhanced Quantum Representation and Qiskit Framework by Alexandru-Gabriel Tudorache, Vasile Manta, Simona Caraiman

“…This paper illustrates the way a proposed quantum voting scheme can be designed in combination with a steganography technique called Least Significant Bit (LSB), by modifying a small number of pixels in multiple grayscale images. …”
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Stego on FPGA: An IWT Approach by Balakrishnan Ramalingam, Rengarajan Amirtharajan, John Bosco Balaguru Rayappan

“…A reconfigurable hardware architecture for the implementation of integer wavelet transform (IWT) based adaptive random image steganography algorithm is proposed. The Haar-IWT was used to separate the subbands namely, LL, LH, HL, and HH, from 8×8 pixel blocks and the encrypted secret data is hidden in the LH, HL, and HH blocks using Moore and Hilbert space filling curve (SFC) scan patterns. …”
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A video steganalysis method based on coding cost variation by Jianyi Liu, Cong Zhang, Ru Zhang, Yi Li, Jie Cheng

“…Experiments show that Motion Vector Coding Cost Change features have higher detection accuracy than Add-or-Subtract-One, Improved Motion Vector Reversion-Based, and other typical features in various steganography methods, and Subtractive Probability of Coding Cost Optimal Matching features have higher detection effect and better robustness than Subtractive Probability of Optimal Matching features.…”
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DDAC: a feature extraction method for model of image steganalysis based on convolutional neural network by Xiaodan WANG, Jingtai LI, Yafei SONG

“…To solve the problem that for image steganalysis based on convolution neural network, manual designed filter kernels were used to extract residual characteristics, but in practice, these kernels filter were not suitable for each steganography algorithm and have worse performance in application, a directional difference adaptive combination (DDAC) method was proposed.Firstly, the difference was calculated between center pixel and each directional pixel around, and 1 × 1 convolution was adopted to achieve linear combinations of directional difference.Since the combination parameters self-adaptively update according to loss function, filter kernels could be more effective in extracting diverse residual characteristics of embedding information.Secondly, truncated linear unit (TLU) was applied to raise the ratio of embedding information residual to image information residual.The model’s coveragence was accelerated and the ability of feature extraction was promoted.Experimental results indicate that substituting the proposed method could improve the accuracy of Ye-net and Yedroudj-net by 1.30%~8.21% in WOW and S-UNIWARD datasets.Compared with fix and adjustable SRM filter kernels methods, the accuracy of test model using DDAC increases 0.60%~20.72% in various datasets, and the training progress was more stable.DDAC-net was proved to be more effective in comparsion with other steganalysis model.…”
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