一种新的基于双伪随机数的图像隐写算法

为提高数字图像隐写中的隐藏信息容量,提出了一种基于双伪随机数的图像隐写算法.首先介绍了伪随机数生成和双像素嵌入信息原理,然后将随机产生的整数伪随机数看作一个辅助像素值,结合载体图像中的一个像素值将两位秘密信息同时嵌入到一个载体图像像素中,从而在像素改变较小的情况下提高隐藏容量.最后分析了算法的嵌入性能,并通过仿真实验证明,该方法在提高隐藏信息容量的同时,也具有很好的安全性能.     

F5隐写算法及其隐写分析研究

图像隐写分析是检测、提取和破坏隐写图像中秘密信息的技术,是信息安全领域的研究热点之一.由Westfeld提出的F5隐写算法是一种重要的图像隐写算法.分析了F5隐写算法及其隐写系统,讨论了一种针对F5隐写算法的隐藏检测方法,并给出了具体实现的算法.实验结果表明,F5算法采用矩阵编码,提高了嵌入效率.     

基于图像相邻像素差值的隐写分析

在研究自然图像统计建模的基础上,结合LSB信息隐写的特点.通过实验发现了原始图像和载密图像在相邻像素差值绝对值和分布对称性的变化,提出了一种基于图像相邻像素差值的隐写分析方法.不但实现了对秘密信息存在性的检测,而且可以估计隐藏的秘密信息的大小.     

一种以AAC压缩音频为载体的隐写方法

通过对AAC编码原理的研究,提出一种基于MDCT量化系数小值区的秘密信息嵌入方法,从而实现了一种能在AAC压缩文件中隐藏大量秘密信息的隐写算法.算法先部分解码载体AAC文件,根据码表搜索出小值区,再通过码字得到一组量化系数,按规则修改每组的最后一个量化系数,然后进行部分编码得到嵌入后的AAC文件.该隐写算法可实现盲提取,且运算复杂度较低.实验结果表明,算法的嵌入容量较高,具有良好的不可感知性,并具有一定的抗隐写分析性,能够抵抗常用的LSB隐写分析方法以及Harmsen提出的基于加性噪声的隐写分析方法.     

针对图像Two-LSBs隐写的分析方法

针对图像Two-LSBs隐写算法,提出了一种新的隐写分析方法.该方法根据Two-LSBs隐写对图像像素相关性的改变来判断秘密信息的有无,同时还可以准确地估计隐写嵌入率和秘密信息的长度.实验结果表明该分析方法的有效性,当嵌入率高于20%时检测正确率可达90%.     

抗隐写密钥分析的LSB隐写算法

LSB算法是一种典型的空间域信息隐藏算法,由于嵌入信息量大、算法简单而成为最常见的信息隐藏算法,也同时成为了隐写分析者很感兴趣的对象。针对隐写位置密钥的攻击,本文提出了一种改进的LSB隐写算法,先在图像各像素的LSB位嵌入噪声信息,再在密钥的控制下有选择性地在部分像素点嵌入隐藏信息。在已知载体图像或已知多幅用同一载体进行信息隐藏的载密图像的情况下,可以有效抵御针对隐写位置密钥的攻击,提高了LSB算法的安全性。同时该思想也可应用于基于DCT域等频域的隐藏算法中。     

基于BN优化SNGAN的自适应音频隐写

音频隐写术是将秘密信息(如文本、图像、音频、视频等)隐藏到载体音频中,不仅能够保证秘密信息本身的安全,而且能保证秘密信息传输的安全,已成为信息隐藏领域的研究热点之一.近年来,基于深度学习的音频隐写分析技术能够在充分挖掘隐写深度特征的基础上实现高效的隐写检测,导致隐写术的安全性降低,为隐写术带来了新的挑战.不过,生成对抗...     

基于LSBMR图像边缘自适应隐写的检测

在图像边缘自适应LSB匹配改进隐写算法中,秘密信息嵌入位置的选择仅由某个方向上像素对的差值决定,未考虑该像素与其邻域内其他像素的差值变化的特点.针对该问题,对隐写前后图像的八方向差分直方图进行分析,提出一种基于LSB匹配改进算法(LSBMR)边缘自适应隐写检测的算法.该算法计算图像的八方向绝对差分直方图,提取直方图中隐写前后变化较为明显的频数用以构建特征向量,并使用支持向量机完成检测.对较低嵌入率下(≤0.5 bpp)的EALSBMR隐写结果进行检测,结果表明该算法的平均检测率均高于现有典型的隐写分析算法.     

基于边缘复杂度和插值法的隐写算法

为了在提高隐写容量的同时保持较好的不可感知性, 依据人眼对图像边缘区域变化不敏感的特性, 提出一种新的自适应隐藏算法。该方案完善了图像边缘复杂度的描述方法, 利用边缘检测理论计算出像素的嵌入强度, 然后通过改进的插值法, 根据嵌入强度, 对图像像素进行插值, 构造出插值点与基准点之间的冗余空间, 从而嵌入相应数据量的秘密信息。实验结果表明, 与传统算法相比, 该方法提高了隐写容量并具有较好的隐蔽性。     

基于图像校准的通用型JPEG隐写分析

对JPEG图像隐写分析而言,直接在嵌入域中提取特征一般会取得更好的效果.然而,在现有的JPEG隐写术中,由于所嵌入秘密信息的能量要远远小于载体图像本身所具有的能量,因而秘密信息嵌入所引起的载体图像微小失真很难直接从给定的待测图像中发现.基于此,文中在已有JPEG图像全局校准方案的基础上,提出了对JPEG图像进行局部校准的新思路.并在此基础上提出了一种全局与局部校准相结合的通用型JPEG隐写分析算法.通过从待测图像和局部校准图像量化后DCT系数的差分信号中提取特征、以及对从待测图像和全局校准图像分别提取的特征进行差分等方式,使得提取的特征对秘密信息的嵌入更为敏感.此外,文中应用Markov转移概率矩阵,分别提取块内以及横向和纵向块间量化后DCT系数在幅值和符号两个方面的相关性作为特征.仿真结果表明,与已有的JPEG隐写分析算法相比,文中所提出的算法具有更好的检测效果.     

Adaptive (<Emphasis Type="Italic">k</Emphasis>, <Emphasis Type="Italic">F</Emphasis><Subscript>1</Subscript>) interpolation-based hiding scheme

In 2012, Lee et al. proposed an interpolation technique with neighboring pixels (INP) as the base to conceal secret information in predicted pixels. Their method can effectively predict the pixel between two neighboring pixels. However, the different lengths of secret messages caused great distortion when a large secret message was concealed in the predicted value. Therefore, the proposed scheme applies the center folding strategy to fold the secret message for reducing image distortion. Furthermore, the proposed scheme references the variance of the neighboring pixel to determine the length of the secret message for controlling image quality. The parameter pair (k, F ₁) is used to categorize the variance and determine the size of the secret message hidden in each category. k is the total number of thresholds which computed based on the characteristics of each image for balancing hiding payload and image quality. F ₁ is the length of the secret message for the smoothest area. The experimental results show that the embedding capacity of the proposed method is 1.5 bpp higher than that of existing methods. For the same hiding payload, the image quality of the proposed method is 1.6 dB higher than that of existing methods.     

A high quality steganographic method with pixel-value differencing and modulus function

In this paper, we shall propose a new image steganographic technique capable of producing a secret-embedded image that is totally indistinguishable from the original image by the human eye. In addition, our new method avoids the falling-off-boundary problem by using pixel-value differencing and the modulus function. First, we derive a difference value from two consecutive pixels by utilizing the pixel-value differencing technique (PVD). The hiding capacity of the two consecutive pixels depends on the difference value. In other words, the smoother area is, the less secret data can be hidden; on the contrary, the more edges an area has, the more secret data can be embedded. This way, the stego-image quality degradation is more imperceptible to the human eye. Second, the remainder of the two consecutive pixels can be computed by using the modulus operation, and then secret data can be embedded into the two pixels by modifying their remainder. In our scheme, there is an optimal approach to alter the remainder so as to greatly reduce the image distortion caused by the hiding of the secret data. The values of the two consecutive pixels are scarcely changed after the embedding of the secret message by the proposed optimal alteration algorithm. Experimental results have also demonstrated that the proposed scheme is secure against the RS detection attack.     

空域序列隐写图像的密钥估计算法*

在已知嵌入消息长度的条件下,隐写密钥可以看做消息嵌入的起始位。将图像像素划分为不同类点,通过分析信息嵌入和最低位置反对各类点的影响,得到图像嵌入信息部分和未嵌入信息部分的差异,最终设计了针对空域序列LSB(least significant bits)隐写图像的密钥估计算法。实验结果表明,该算法可对隐写密钥进行快速有效的估计。     

Reversible data hiding for high quality images exploiting interpolation and direction order mechanism

Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images.     

彩色图像大容量时域隐写

提出一种彩色图像大容量信息隐藏时域算法。利用人类视觉系统的视见、颜色宽容特性,结合不同的秘密信息位,将彩色图像载体相邻两个像素点红色分量的颜色值作较小的调整,达到在彩色图像载体中隐藏秘密信息的目的。结果证明,该算法信息隐藏容量大,透明性好,健壮性较好,能经受添加噪声、剪切、格式转换等图像处理及攻击。     

基于像素交换及时空混沌映射的信息隐藏方法

提出了一种在图像载体中进行信息隐藏的新方法。该方法通过硬c均值聚类分析,确定可嵌信息区域,在可嵌信息区域内的相邻像素间通过像素交换来编码信息。采用时空混沌置乱技术,控制秘密信息的嵌入过程,并对嵌入信息进行加密。该方案具有较好的视觉隐蔽性及统计隐蔽性,并且密钥空间大,实现了算法可公开的信息隐藏。     

Adaptive Data Hiding,Using Pixel-Value-Differencing and LSB Substitution

With the development of Internet communications, the security of message sending on the Internet has become very important. This article proposes a new adaptive data hiding method with a large data-embedding capacity for gray-scale images to raise the security of sending a message between sender and receiver in networks. At first, the image is divided into some blocks consisting of two consecutive pixels. If the values of both pixels are small, fewer secret bits will be embedded within the two pixels, otherwise, the difference value of two pixels is calculated, and according to the obtained difference value, the method will estimate the number of embedding bits into LSBs of two pixels. This number is adaptive and depends on the range to which the difference value belongs. A readjusting phase is presented to keep the difference of value pixels in the same range before and after embedding. Experimental results show that our method has increased the capacity of embedding bits in comparison with the several other methods.     

图像LSB密写的信息隐藏量分析

介绍了一种基于统计特性的LSB密写分析方法,对其进行了改进并提出了可靠估计信息隐藏长度的方法。该方法利用相邻像素相关性定义了统计量,可根据阈值判断秘密信息的有无。对待检测图像进行二次嵌入,根据统计量的变化建立模型,能可靠估计秘密信息隐藏长度。实验表明,估计出的信息量比较准确。     

基于数字调制的信息隐藏算法

将数字图像置乱技术中的幻方变换与数字通信中的数字调制技术相结合，提出一种新的文字信息隐藏算法。以二值文字图像为待隐藏的秘密信息，以静止图像为隐秘载体。算法针对二值文本图像，首先用幻方变换对其进行置乱预处理，并用一数值控制置乱次数，在提取时作为密匙；然后对作为隐秘载体的原始图像作分块离散余弦变换，根据每个分块灰度值的方差与秘密信息进行块匹配；根据秘密信息的值对原始图像的分块余弦值进行数字调制嵌入信息。实验表明该算法实现的隐藏图像透明性好，具有良好的抗剪切性。对不同的量化阶数下，对秘密信息的提取进行了实验比较。     

An Improved Histogram-Shifting-Imitated reversible data hiding based on HVS characteristics

In this paper, we propose a reversible data hiding scheme to hide a secret message into a cover image by considering the characteristics of Human Visual System (HVS) in order to improve the visual imperceptibility. The human eyes are more sensitive to the changes in the low intensity pixels than the higher intensity ones. Therefore, we divide the intensity levels (0–255) into four groups: the first group contains 0–79 intensity level; second, third, and fourth group contain, respectively, 80–151, 152–215, and 216–255 intensity levels. We further divide first group into segments of size 2 elements, second, third, and fourth group into 3, 4, and 5 elements sized segments, respectively. After constructing the segments, we scan the image in raster order to identify the peak points for each segment, which are used to embed the secret data. The secret data is also divided into the four segments according to the identified peak points per group. The first segment data is converted into base2 representation, second, third and fourth segment secret data into 3, 4, and 5 base representation, respectively. The first segment of secret data is embedded into the peak points belonging to first group, second, third and fourth group secret data is embedded into the peak points of second, third and fourth group, respectively. Thus, our scheme makes least changes into the pixels belonging to the first group which have least intensity values and most to the fourth group pixels which have highest intensity values. Experimentally, our scheme provides better quality stego image and hides more secret data than the other state of the art schemes. We also build a location map for all the peak points to ensure the reversibility of the proposed scheme.