基于Arnold变换与改进LSB嵌入方案的信息伪装算法

文章提出了一种基于二维Arnold变换与改进LSB嵌入方案的图像信息伪装算法,在对图像进行二维Arnold变换的基础上,采用改进的LSB嵌入方案嵌入数据,提取时只需提取Arnold变换图像的LSB即可。该算法结合了图像置乱技术和改进的LSB嵌入方案,对嵌入的数据形成了双层保护。实验结果表明,该算法的数据嵌入量及失真度与传统的LSB嵌入方式一致,同时能够有效地抵抗RS(RegularSingular)和SPA(SamplePairAnalysis)隐写分析,并保持了图像的直方图统计特征,此外,该方法适用于灰度图像和彩色图像,易于实现。     

基于混沌和脆弱水印的图像篡改检测算法

针对现有基于脆弱水印方法的不足,提出了一种新的结合混沌系统和脆弱水印的图像篡改检测算法。算法首先利用Arnold cat映射对原始图像进行k次置乱,然后选取置乱图像的最低有效位(LSB)平面作为水印嵌入位置,实际嵌入的水印由Logistic混沌映射产生的随机二进制序列与原始水印异或得到,通过LSB替换算法嵌入。最后对LSB替换后图像进行T-k次的Arnold cat映射得到水印图像。实验结果表明,混沌系统的引入大大增强了脆弱水印的安全性;另外,针对不同种类的攻击,算法具有良好的篡改检测和定位精确性。     

基于LSB图像隐藏系统的设计与实现

文中运用Matlab实现了基于空域LSB(Least Significant Bit)的灰度图像隐藏与提取系统。图像隐藏系统由置乱模块、加密模块和嵌入模块组成。置乱模块采用基于行列置换的置乱算法,经过多次迭代处理,将原始图像变换为灰度均衡的灰度图像,迭代的次数作为密钥一。加密模块借鉴通信系统中常用的伪随机序列加密的方法,运用软件产生m序列对置乱后的图像进行加密处理。m序列的初始值作为密钥二。经过置乱、加密后的图像进入嵌入模块,采用最低位隐藏方法将数据信息嵌入到载体图像中。图像信息提取系统则由解隐藏、解密和反置乱三部分组成。     

基于纠错编码的图像篡改恢复方法的研究

利用具有纠错功能的汉明码和置乱技术,提出了一种基于纠错编码技术与LSB结合的图像内容篡改恢复方法。提取图像的原始特征作为信息源码生成校验码,将生成的校验码经Arnold置乱后嵌入原始图像。当水印图像被篡改后,根据提取的校验码恢复图像的原始特征。实验结果表明,该算法对图像局部发生的篡改可以有效地检测并定位,并且具有较好的自恢复功能。     

基于置乱变换的多重数字水印盲算法

提出了一种新的基于置乱变换的多重数字水印盲算法。该算法具有以下性能：(1)可嵌入多重水印，标志不同所有者（如创作者、发行者、使用者等）版权使用的合法信息；(2)水印的隐藏效果好，多重水印的嵌入不会造成视觉质量的严重下降；(3)水印的嵌入和提取过程中需要个人密钥，不知道密钥的非法使用者无法正确提取水印；(4)水印的嵌入位置只依赖于密钥，与算法无关，非法用户无法知道水印的嵌入位置；(5)水印的提取无需原始图像和原始水印；(6)可以抵抗LSB攻击和剪切攻击。     

数字图像水印嵌入和提取的平稳小波变换方法

提出一种基于离散平稳小波变换的变换域的数字图像水印嵌入和提取算法。本算法先将数字水印图像进行置乱变换(Arnold变换),然后将置乱后的水印图像嵌入到平稳小波变换后的图像中,最后将提取出的水印图像进行Arnold反置乱变换得到原始水印图像。由于本算法选择了合适的水印嵌入位置,实验结果表明,该算法不但使水印具有很好的不可见性,而且所嵌入的水印对一般的图像处理如噪声、滤波、旋转、压缩等有很强的鲁棒性。     

一种改进的LSB数字图像隐藏算法*

目前针对常用的LSB信息隐藏,SPA分析(sample pair analysis)和RS方法(regularand singular groups method)能以很高的精度估计出图像中隐藏信息的比率。基于几何变换的性质,提出了一种可用于图像置乱技术的亚仿射变换,并利用矩阵编码思想改进LSB的嵌入方式,从而使嵌入数据获得了较好的抗隐写分析性能。实验结果表明,该算法能有效抵抗RS和SPA隐写分析,并保持图像的直方图统计特征,且适用于灰度图像和彩色图像,易于实现。     

基于图像置乱和小波变换的零水印算法

传统的数字水印方法在嵌入水印时都要对原始图像数据进行一定的修改导致嵌入水印图像的保真度下降.提出了一种基于仿射变换置乱与小波变换的零水印算法,该算法对嵌入的水印图像进行置乱,选择被嵌入图像的小波变换的低频子图与置乱的水印图像进行运算,对运算结果进行循环移位产生密钥图像.而小波变换的低频子图集中了图像的主要特征,所以该水印算法对各种攻击(例如:加噪,滤波,JPEG压缩,剪切)具有很高的鲁棒性,而且产生的水印为灰度图像而不是二值序列,具有很好的检测精度.仿真实验表明该算法的鲁棒性优于现有算法,而且在抗各种常见攻击方面性能良好.     

一种基于混沌和置乱的DCT域图像数字水印算法

文章提出了一种基于混沌和置乱的DCT(离散余弦变换)域图像数字水印算法。该算法是利用Arnold变换将水印图像进行置乱,然后利用logistic混沌技术生成混沌序列,加入到Arnold置乱后的水印图像中形成密文,最后嵌入到原始图像中的数字水印算法。实验结果表明此算法使水印的嵌入达到了较好的鲁棒性和不可见性。     

基于细胞神经网络和并行压缩感知的 图像加密算法

基于细胞神经网络(CNN)和并行压缩感知(CS)提出了一种高安全性的非可视化图像加密算法, 旨在提高现有加密算法的信息传输效率以及减少存储空间。首先明文图像的小波系数经过阈值处理和索引置乱 后,利用受控的部分哈达玛矩阵对其进行并行压缩,接着执行费雪耶兹行列置乱和加模操作,然后再将部分加 密图像分割并通过最低有效位(LSB)嵌入算法随机地隐藏到剩余加密图像的 alpha 通道中生成最终的类噪声密 文图像,具有超混沌特性的 CNN 所产生的伪随机序列用于构造置乱、扩散以及受控测量矩阵。最后,通过一 系列的安全性分析表明,该算法具有很高的传输效率和安全性。     

基于污染数据分析实现LSB秘密消息的检测

信息隐藏技术已经成为网络信息安全的一个重要研究方向，如何有效地监控和检测网络中传递的秘密消息对于保障国家安全具有重要的现实意义．针对互联网上大量的隐写软件利用彩色厦灰度图像的最低有效比特位（LSB）隐藏秘密消息，基于污染数据分析，提出了一种新的隐写分析方法，并给出了此算法的数学模型．该方法不仅可以快速有效地检测出图像中秘密消息的存在性，同时还可以精确地估计出连续及随机间隔嵌入算法下所嵌入秘密消息的长度．     

一种可抵御RS 统计分析的图像信息隐藏方案

通过动态补偿隐藏信息后的图像，给出一种可抵御RS分析的LSB隐藏方案．该方案基于混沌系统产生随机序列选择嵌入位置并进行LSB嵌入，对嵌入信息后的图像进行动态补偿，补偿后的图像即使信息嵌入率接近于100％，RS方法得到的估计值仍将低于判决阈值，从而作出错误判决．混沌系统初值和动态补偿参数可进一步提高系统的安全性．实验表明，该方案可有效抵抗经典RS方法及其多种改进方法的分析．     

Inverted pattern approach to improve image quality of information hiding by LSB substitution

Capacity and invisibility are two targets of the methods for information hiding. Because these two targets contradict each other, to hide large messages into the cover image and remain invisible is an interesting challenge. The simple least-significant-bit (LSB) substitution approach, which embeds secret messages into the LSB of pixels in cover images, usually embeds huge secret messages. After a large message is embedded, the quality of the stego-image will be significantly degraded. In this paper, a new LSB-based method, called the inverted pattern (IP) LSB substitution approach, is proposed to improve the quality of the stego-image. Each section of secret images is determined to be inverted or not inverted before it is embedded. The decisions are recorded by an IP for the purpose of extracting data and the pattern can be seen as a secret key or an extra data to be re-embedded. The experimental results show that our proposed method runs fast and has better results than that of previous works.     

基于图像平滑度的空域LSB嵌入的检测算法

对图像像素值与邻域均值的差的分布进行建模,以该分布的方差定义了图像平滑度的概念,进而通过对消息嵌入、LSB平面取反带来的图像平滑度的变化进行分析,提出了针对空域LSB替换伪装算法的秘密消息长度估计算法,该算法可以准确地估计图像中嵌入的秘密信息数据量的大小.文中算法物理意义直观、实现简单、计算量小、计算速度快,有利于实现实时检测.实验结果表明该方法是有效的.     

Combining LSB embedding with modified Octa-PVD embedding

This paper proposes a new image steganographic method that effectively combines LSB embedding with Octa-PVD embedding. A cover image is divided into non-overlapping 3?×?3 sub-blocks, the n least significant bits of the center pixel of each sub-block is first substituted by secret data (n-LSB substitution). Then, the differences between the center pixel and its eight neighbors are calculated. For each direction, if the difference is equal or larger than a threshold (predefined by users or automatically determined by image analysis), secret data is embedded into the neighbor pixel by n-LSB substitution. Otherwise, secret data is embedded by PVD embedding, but into the neighbor pixel only. Consequently, depending on the conditions of each sub-block, a single embedding method can be used to the whole sub-block, or two embedding methods can be used alternately within a sub-block. Comparisons with existing LSB or multi-directional PVD embedding methods demonstrate that the proposed method has more optimized and higher embedding capacity and PSNR.

     

Quantitative steganalysis of digital images: estimating the secret message length

The objective of steganalysis is to detect messages hidden in cover objects, such as digital images. In practice, the steganalyst is frequently interested in more than whether or not a secret message is present. The ultimate goal is to extract and decipher the secret message. However, in the absence of the knowledge of the stego technique and the stego and cipher keys, this task may be extremely time consuming or completely infeasible. Therefore, any additional information, such as the message length or its approximate placement in image features, could prove very valuable to the analyst. In this paper, we present general principles for developing steganalytic methods that can accurately estimate the number of changes to the cover image imposed during embedding. Using those principles, we show how to estimate the secret message length for the most common embedding archetypes, including the F5 and OutGuess algorithms for JPEG, EzStego algorithm with random straddling for palette images, and the classical LSB embedding with random straddling for uncompressed image formats. The paper concludes with an outline of ideas for future research such as estimating the steganographic capacity of embedding algorithms.     

Steganalysis of LSB matching based on statistical modeling of pixel difference distributions

This paper presents a least significant bit (LSB) matching steganography detection method based on statistical modeling of pixel difference distributions. Previous research indicates that natural images are highly correlated in a local neighborhood and that the value zero appears most frequently in intensity differences between adjacent pixels. The statistical model of the distribution of pixel difference can be established using the Laplace distribution. LSB matching steganography randomly increases or decreases the pixel value by 1 when the message is embedded; thus, the frequency of occurrence of the value zero in pixel differences changes most dramatically during message embedding. Based on the Laplacian model of pixel difference distributions, this paper proposes a method to estimate the number of the zero difference value using the number of non-zero difference values from stego-images and uses the relative estimation error between the estimated and actual values of the number of the zero difference value as the classification feature. Experimental results indicate that the proposed algorithm is effective in detecting LSB matching steganography and can achieve better detection performance than the local extreme method under most circumstances.