一种基于汉明码和湿纸码的隐写算法

该文通过将载体图像分割成矩阵块,重复利用载体矩阵块像素,结合汉明码和湿纸码构造了一种新的双层结构隐写算法。该算法首先利用汉明码在载体矩阵的行向量中嵌入信息,然后在列向量上根据是否影响前面嵌入结果以及是否需要3个修改引入dry和wet的概念,并通过构造伪随机二值矩阵,采用湿纸码在列向量上实现二次嵌入,从而获得较好的隐写性能。实验结果表明:该隐写算法在嵌入率为0.1至0.8 bpp范围内,性能优于PPC和F5算法。     

基于Canny边缘检测的自适应空域隐写术

针对自适应空域隐写术设计的关键问题,该文结合Canny边缘检测和校验格编码(STC)提出一种不需要同步边信息的自适应空域隐写方法。首先,根据秘密消息长度、载体图像等因素确定Canny边缘检测算法中的参数取值,进而根据相应的参数取值使用Canny边缘检测算法来选择载体图像的边缘区域。然后,分别定义边缘区域像素和非边缘区域像素的嵌入失真;最后,在载体像素的多个最低有效位平面(LSB)使用STC嵌入秘密消息。实验结果表明:该隐写方法在4种嵌入率情况下抵抗常见通用隐写分析的性能优于3种已有的隐写方法,且在较小嵌入率情况下与空域通用小波相对失真方法(S-UNIWARD)相当。     

一种基于像素块的纹理优先自适应隐写算法

与平坦区域相比,图像纹理区域在结构上表现出更多的随机性,因此将密信嵌入到纹理丰富的区域可获得更好的安全性.本文利用相邻像素的LSB与次低LSB位之间的关系,提出一种基于像素块的纹理优先自适应隐写算法,将密信优先嵌入到复杂纹理区域.所设计的纹理判别准则能结合待嵌入密信长度,自适应选择嵌入区域.针对在嵌密过程中嵌密块可能出现的异常情况,提出一种像素值调整方案,并从理论上证明了其可行性.实验结果表明本文算法比两种经典的LSB算法和一种现有的基于边缘优先的自适应算法具有更高的嵌入效率,且对四种有代表性的隐写分析算法通常具有更强的抵御能力.     

一种基于扩展加减覆盖集的隐写方法

G-LSB-M隐写方法是一种±1隐写嵌入方法,通过减少嵌入时的修改次数提高隐写的嵌入效率.该方法嵌入时所用的加减覆盖集只能通过穷举搜索构造,当嵌入消息分段长度n较大时,穷举搜索的计算代价过高导致无法实现.为了解决这一问题,本文提出了基于扩展加减覆盖集的隐写方法,通过从基础加减覆盖集中去除若干非必需的元素,能够以较小的计算代价构造出扩展加减覆盖集,避免了G-LSB-M方法中的穷举搜索困难,使得使用更长的信息分段进行嵌入成为可能.该方法降低了隐写时的平均修改次数,提高了嵌入效率和隐写的隐蔽性.     

基于F5与湿纸码相结合的密写算法研究

基于F5密写与湿纸码提出了一种具有较高不可觉察性的信息隐藏算法.首先用方差将图像划分为不同的区域,利用湿纸码在低、中频的量化后小数部分为[0.4,0.6]的DCT系数构造选择信道,并且要求它们不处于色块区域.其次在进行嵌入信息时增加DCT系数的绝对值.该算法避免了对人眼视觉敏感区域的修改以及F5密写的“收缩”现象,与F5密写相比改进了系数选择方法与嵌入策略.实验表明,该算法具有较高的安全性,含密图像具有较好的图像质量.     

基于Arnold变换的数字图像自适应隐写算法

以往的图像自适应隐写算法大多数以顺序满嵌的方式嵌入秘密信息,这类算法秘密信息的隐蔽性不够高,因此提出一种随机非满嵌算法。通过分析出图像的系统参数使图像的满嵌容量刚好大于秘密信息的长度让载体图像达到非满嵌,增强了隐写的灵活性,减少了载体图像的嵌入修改量。再使用Arnold变换对数据的嵌入顺序进行置乱,防止攻击者按顺序分析出秘密信息,使秘密信息的隐蔽性变高,进而提高了算法的安全性。实验结果表明本算法提高了隐写的隐蔽性,减少了图像的嵌入失真度,且随机非满嵌操作适用于很多同类算法。     

基于Hilbert填充曲线的自适应隐写

 自适应隐写用于将适量的消息比特嵌入到载体以取得感知质量和容量的最佳折衷.本文提出一种基于量化嵌入机制的自适应隐写方法,并基于该方法将秘密消息比特嵌入到由Hilbert填充曲线顺序构造的三像素组的两像素差中.由于充分利用图像本身的感知特性构造了量化嵌入使用的分割码本,所提算法在感知质量和容量上具有较好的综合性能.     

基于HCF统计特征的MIDI音频隐写分析

针对乐器数字接口（MIDI）音频三种常见的LSB隐写方法：最低位替换、最低位匹配和低两位替换隐写,为了提高隐写检测正确率,提出基于直方图特征函数（HCF）统计特征和支持向量机（SVM）的隐写分析方法,通过提取MIDI音频力度分量直方图特征函数域21维特征,用支持向量机训练分类器对MIDI音频进行分类。实验表明,当嵌入率大于10%情况下,此隐写分析方法对三种LSB隐写方法的平均分类正确率达90%以上。     

基于MED信道选择和虚拟嵌入块的YASS改进算法

为抵抗YASS隐写分析算法,本文提出一种新的YASS改进算法。该算法首先利用密钥选择不规则的区域,生成一个虚拟的8×8嵌入块;然后根据图像自身特点,提出一种最小化嵌入失真的计算方法,对嵌入块修改后的量化DCT系数进行失真分析,选择失真影响最小的交流DCT系数进行秘密信息嵌入,取代传统方法直观选择前19交流DCT系数。将文中改进算法与虚拟嵌入块YASS（VH-YASS）算法进行了对比实验,实验结果证明,依据嵌入失真由小到大的顺序选择嵌入信道,在抵抗隐写分析和视觉质量方面都优于VH-YASS隐写方法。     

一种基于LSB序列局部特征的通用隐写检测方法

基于短重码间距统计的隐写检测方法对LSB匹配等隐写技术有良好的检测性能.然而该方法为适应不同的应用场合,需要选择适当的短重码维数.这种一元统计分析方法无法考虑多个特征之间存在的联系,从而影响检测能力.本文分析证明了单个短重码间距统计变量的检测能力规律,给出了可减少检测次数的合理选择短重码维数的方法.基于短重码间距统计特征变量之间的相关性选择特征子集,构造局部特征描述向量,进而提出一种基于LSB序列局部特征的通用隐写检测方法.该方法采用GMM生成模型描述多维局部特征,并基于全局序列词汇设计融合GMM生成模型与SVM判别方法的分类器.实验结果表明:本文方法在有效控制虚警率的前提下,对LSB匹配隐写和LSB替换隐写都有较好的检测性能.     

一种可抵抗RS掩密分析方法的掩密算法

Fridrich提出的RS掩密分析方法,适合于检测采用随机嵌入的LSB掩密算法,不但可以检测信息的存在,还可以检测出嵌入信息的长度。文中对现有的空域LSB掩密算法加以改进,使改进后的算法可以抵抗RS攻击,从而进一步提高了LSB掩密算法的安全性。     

基于粒子群算法和改进PM1的JPEG图像中的安全密写方法

PMI（加、减1）是LSB密写方法的一种改进,它的嵌入和提取几乎和LSB一样简单,却提供了更好的安全性。文中基于JPEG图像的属性对PM1进行改进,并结合粒子群算法（particle swarm optimization,PSO）提出了一种用于JPEG图像的高安全性和高容量的密写方法。充分的实验表明,该方法在保持分块效应和直方图,以及高容量方面都优于现有的JPEG图像中的经典密写算法。     

Perfectly Secure Steganography: Capacity, Error Exponents, and Code Constructions

An analysis of steganographic systems subject to the following perfect undetectability condition is presented in this paper. Following embedding of the message into the covertext, the resulting stegotext is required to have exactly the same probability distribution as the covertext. Then no statistical test can reliably detect the presence of the hidden message. We refer to such steganographic schemes as perfectly secure. A few such schemes have been proposed in recent literature, but they have vanishing rate. We prove that communication performance can potentially be vastly improved; specifically, our basic setup assumes independent and identically distributed (i.i.d.) covertext, and we construct perfectly secure steganographic codes from public watermarking codes using binning methods and randomized permutations of the code. The permutation is a secret key shared between encoder and decoder. We derive (positive) capacity and random-coding exponents for perfectly secure steganographic systems. The error exponents provide estimates of the code length required to achieve a target low error probability. In some applications, steganographic communication may be disrupted by an active warden, modeled here by a compound discrete memoryless channel (DMC). The transmitter and warden are subject to distortion constraints. We address the potential loss in communication performance due to the perfect-security requirement. This loss is the same as the loss obtained under a weaker order-1 steganographic requirement that would just require matching of first-order marginals of the covertext and stegotext distributions. Furthermore, no loss occurs if the covertext distribution is uniform and the distortion metric is cyclically symmetric; steganographic capacity is then achieved by randomized linear codes. Our framework may also be useful for developing computationally secure steganographic systems that have near-optimal communication performance.     

Block-Based Adaptive Image Steganography Using LSB Matching Revisited

Recently, an edge adaptive image steganographic method based on least significant bit (LSB) matching revisited (EA-LSBMR) has been proposed, which holds good visual quality and proper security under appropriate embedding rates. However, from the extensive experiments to EA-LSBMR, we find that the discrete Fourier transform (DFT) spectrum of pixelpairs differences histogram still reveals the presence of a secret message even in a low embedding rate. To enhance the security, a modified scheme is proposed in this paper, which can defeat the above-mentioned analysis and keep the visual quality better than EA-LSBMR in higher embedding rates. Experimental results using a latest universal steganalysis method have demonstrated the proposed method's good performance.     

隐写术中矩阵编码的保密安全性

针对矩阵编码在隐写码和湿纸码中的应用,基于信息论模型研究矩阵编码在不同攻击条件下的保密安全性。在已知载体攻击条件下,给出矩阵编码的密钥疑义度、消息疑义度和密钥的唯一解距。在选择载密攻击条件下,指出只需n个差分方程组即可恢复矩阵编码的共享密钥。     

Integrated encoding with high efficiency for digital steganography

Three different encoding mechanisms are combined to improve further steganographic embedding efficiency. They are secret-bit representation derived from the parity check coding, exploitation of the modification direction on pixel-values, and wet paper coding. The parity of least significant bit weight in each pixel-group is used to accommodate one secret bit. The weighted-sums of all pixel-groups and wet paper coding are used to select which pixels are modified and decide the way of modification as to whether to add or subtract one for carrying more secret data. It is shown that, by taking full advantage of these mechanisms, the embedding efficiency of the proposed scheme is higher than any of the previous steganographic embedding techniques.     

High capacity image steganographic model

Steganography is an ancient art of conveying messages in a secret way that only the receiver knows the existence of a message. So a fundamental requirement for a steganographic method is imperceptibility; this means that the embedded messages should not be discernible to the human eye. There are two other requirements, one is to maximise the embedding capacity, and the other is security. The least-significant bit (LSB) insertion method is the most common and easiest method for embedding messages in an image. However, how to decide on the maximal embedding capacity for each pixel is still an open issue. An image steganographic model is proposed that is based on variable-size LSB insertion to maximise the embedding capacity while maintaining image fidelity. For each pixel of a grey-scale image, at least four bits can be used for message embedding. Three components are provided to achieve the goal. First, according to contrast and luminance characteristics, the capacity evaluation is provided to estimate the maximum embedding capacity of each pixel. Then the minimum-error replacement method is adapted to find a grey scale as close to the original one as possible. Finally, the improved grey-scale compensation, which takes advantage of the peculiarities of the human visual system, is used to eliminate the false contouring effect. Two methods, pixelwise and bitwise, are provided to deal with the security issue when using the proposed model. Experimental results show effectiveness and efficiency of the proposed model     

基于遗传优化图像稀疏分解的密写算法

根据超完备字典图像稀疏表示的稀疏性和特征保持性,提出了基于遗传优化图像稀疏分解的密写算法。该密写算法将信息隐藏与基于图像稀疏分解的压缩过程合二为一。首先在基于MP的图像稀疏分解每步迭代中,采用遗传算法快速实现最佳匹配原子的选取;对稀疏分解得到的结果用不同的量化位数进行量化;最后采用LSB嵌入方式将秘密信息隐藏于量化后参数的不同最低有效位中,得到载密图像。实验结果表明,本文提出的基于遗传优化图像稀疏分解的密写算法具有良好的视觉效果, 与相同嵌入容量的经典空域和DCT域LSB算法相比,本文的密写算法获得了更高的抵抗隐写分析能力。抗隐写分析实验也表明新的密写算法对嵌入位数不敏感,可灵活地扩充嵌入容量。