Results 31 to 40 of about 6,801,187 (249)
Green Steganalyzer: A Green Learning Approach to Image Steganalysis [PDF]
APSIPA Transactions on Signal and Information Processing, 2023 A novel learning solution to image steganalysis based on the green learning paradigm, called Green Steganalyzer (GS), is proposed in this work. GS consists of three modules: 1) pixel-based anomaly prediction, 2) embedding location detection, and 3 ...
Yao Zhu +4 more
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Improvement of convolutional neural network structure for image steganalysis [PDF]
Jisuanji gongcheng, 2018 Aiming at the situation that the accuracy of image steganalysis is not high,a steganalysis model of Convolutional Neural Network(CNN) based on Multi-layer percepual convolution layer(Mlpconv) is constructed.The model uses multi-layer perceptual ...
GAO Peixian,WEI Lixian,LIU Jia
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Steganalysis in resized images [PDF]
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 It is well known that the security of a given steganographic algorithm strongly depends on the statistical properties of the cover source. In this paper, we study how downsampling affects steganographic security. The secure payload no longer scales according to the square-root law because resizing changes the statistical properties of the cover source.
Jan Kodovský, Jessica J. Fridrich
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Comprehensive Criteria-Based Generalized Steganalysis Feature Selection Method
IEEE Access, 2020 Redundant steganalysis feature components in high-dimensional steganalysis feature of images increase the spatio-temporal complexity of steganalysis and even reduce the detection accuracy of the stego images.
Yihao Wang +4 more
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Extensible Steganalysis via Continual Learning
Fractal and Fractional, 2022 To realize secure communication, steganography is usually implemented by embedding secret information into an image selected from a natural image dataset, in which the fractal images have occupied a considerable proportion.
Zhili Zhou +3 more
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Spatial Steganalysis Based on Non-Local Block and Multi-Channel Convolutional Networks
IEEE Access, 2022 Image steganalysis aims to detect whether secret information is hidden in images and is a means to solve the communication security. Recently, a series of convolutional neural network-based steganalysis models has been proposed and has achieved ...
Xu Han, Tao Zhang
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Consensus-Clustering-Based Automatic Distribution Matching for Cross-Domain Image Steganalysis
IEEE Transactions on Knowledge and Data Engineering, 2023 Image steganalysis is a technique to detect whether an image contains hidden information. Although the existing cross-domain steganalysis methods have been presented to narrow the distribution gap between different domains, it is still challenging to ...
Ju Jia +4 more
semanticscholar +1 more source
IET Image Processing, 2023 The steganalysis for JPEG image is an important research topic, as the enormous popularity of JPEG image on Internet. However, the stego noise feature extraction process of the existing deep learning‐based steganalytic methods are not adaptive enough to ...
Wentong Fan +4 more
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Quantized Gaussian JPEG Steganography and Pool Steganalysis
IEEE Access, 2022 Currently, algorithms for compressed image steganography mainly embed hidden message by minimizing the resulting distortion or statistical detectability.
Mohammed Aloraini +2 more
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GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis
IEEE Access, 2021 Advances in Deep Learning (DL) have provided alternative approaches to various complex problems, including the domain of spatial image steganalysis using Convolutional Neural Networks (CNN).
Tabares-Soto Reinel +9 more
semanticscholar +1 more source