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Steganalysis by subtractive pixel adjacency matrix and dimensionality reduction

Science China(Information Sciences) 2014年第4期57卷 286-292页

作者： ZHANG Hao PING XiJian XU ManKun WANG Ran Department of Signal and Information Processing Zhengzhou Information Science and Technology Institute

Subtractive pixel adjacency matrix(SPAM)features,introduced by Pevn′y et *** a type of Markov chain features,are widely used for blind steganalysis in the spatial *** this paper,we present three improvements to SPAM as follows:1)new features based on parallel subtractive pixels are added to the SPAM features,which only refer to collinear subtractive pixels;2)features are extracted not only from the spatial image,but also from its grayscale-inverted image,making the feature matrices symmetrical and reducing their dimensionality by about half;and 3)a new kind of adjacency matrix is used,thereby reducing about 3/4 of the dimensionality of the *** results show that these methods for dimensionality reduction are very effective and that the proposed features outperform SPAM.

关键词： steganalysis Markov chain dimensionality reduction lsb matching YASS algorithm

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A Robust Data Hiding Reversible Technique for Improving the Security in e-Health Care System

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 201-219页

作者： Saima Kanwal Feng Tao Ahmad Almogren Ateeq Ur Rehman Rizwan Taj Ayman Radwan School of Computer and Communication Lanzhou University of TechnologyLanzhou730050China Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11633Saudi Arabia Department of Electrical Engineering Government College UniversityLahore54000Pakistan Instituto de Telecomunicaoes and Universidade de Aveiro Aveiro3810-193Portugal

The authenticity and integrity of healthcare is the primary *** reversible watermarking schemes have been developed to improve the primary objective but increasing the quantity of embedding data leads to covering image distortion and visual quality resulting in data security detection.A trade-off between robustness,imperceptibility,and embedded capacity is difficult to achieve with current algorithms due to limitations in their *** this purpose insight,an improved reversibility watermarking methodology is proposed to maximize data embedding capacity and imperceptibility while maintaining data security as a primary concern.A key is generated by a random path with minimum bit flipping is selected in the 4 × 4 block to gain access to the data embedding *** random path's complex structure ensures data *** of various sizes(8 KB,16 KB,32 KB)are used to analyze image imperceptibility and evaluate quality *** proposed reversible watermarking methodology performance is tested under standard structures PSNR,SSIM,and *** results revealed that the MRI watermarked images are imperceptible,like the cover image when lsb is 3 bits *** proposed reversible watermarking methodology outperforms other related techniques in terms of average PSNR(49.29).Experiment results show that the suggested reversible watermarking method improves data embedding capacity and imperceptibility compared to existing state-of-the-art approaches.

关键词： Medical images security data hiding lsb matching hiding capacity imperceptibility

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基于逐像素概率预测的图像隐写定位研究

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计算机工程与应用 2022年第12期58卷 85-93页

作者：陈升李智贵州大学计算机科学与技术学院贵阳550025

为进一步增强图像隐写分析的实用性,对内容自适应隐写术和非内容自适应lsb matching的隐写像素定位问题展开研究,提出一种端到端的图像隐写定位网络PSL_NET,在输入端输入一张图像,输出端定位出图像的隐写像素的位置。在预处理层中,利用... 详细信息

为进一步增强图像隐写分析的实用性,对内容自适应隐写术和非内容自适应lsb matching的隐写像素定位问题展开研究,提出一种端到端的图像隐写定位网络PSL_NET,在输入端输入一张图像,输出端定位出图像的隐写像素的位置。在预处理层中,利用空域富模型的高通滤波器提取残噪图像;在深度残差层中,通过深度残差学习增强隐写特征的表达能力;在像素预测层中,利用标记出隐写像素实际位置的掩码图像进行有监督地学习,增强网络对局部隐写像素的感知能力,无区别对待平滑或者纹理区域的像素,逐一预测图像每位像素是真实位或是隐写位,最终预测出图像的隐写像素位;从目标函数层面解决正负样本的不均衡问题,提升检测精度。在基于BOSSbase v1.01数据源展开的实验中,该网络对经自适应隐写术S-UNIWARD在负载为0.4 BPP嵌入的隐写图像的像素检测准确度为0.98174,实验验证该网络同时适用于对经非内容自适应隐写术lsb matching嵌入后的隐写图像进行隐写像素定位。

关键词：图像隐写分析内容自适应隐写术 lsb matching 深度学习隐写定位

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A Blind Detection Resistant Steganographic Algorithm for Images Based on Texture Complexity and Pixel-value Differencing

A Blind Detection Resistant Steganographic Algorithm for Ima...

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2012年计算机应用与系统建模国际会议

作者： Tao Ran Zhang Tao ZhengZhou Information Science and Technology Institute

According to the analysis of the effect of the texture complexity on steganalysis, we propose a data hiding algorithm based on texture complexity and difference pixel value. Firstly, the image is decomposed into blocks, after which the texture complexity of each block is calculated and blocks with high complexity are selected. Then the different pixel values on two directions of the selected blocks are computed to choose the edge areas. The secret messages are only embedded in the pixel-value differencing above the threshold. When compared with several steganographic methods on different image databases, the experimental results show that our method outperforms previous steganographic methods such as lsb matching and Adaptive data hiding in edge areas of images on the capability of resisting universal blind detecting methods, such as wavelet high-order statistics analysis.

关键词： Steganography Universal blind detection Texture complexity Edge area lsb matching

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