An Image Steganography Algorithm Based on Quantization Index Modulation Resisting Scaling Attacks and Statistical Detection

In view of the fact that the current adaptive steganography algorithms are difficult to resist scaling attacks and that a method resisting scaling attack is only for the nearest neighbor interpolation method,this paper proposes an image steganography algorithm based on quantization index modulation resisting both scaling attacks and statistical detection.For the spatial image,this paper uses the watermarking algorithm based on quantization index modulation to extract the embedded domain.Then construct the embedding distortion function of the new embedded domain based on S-UNIWARD steganography,and use the minimum distortion coding to realize the embedding of the secret messages.Finally,according to the embedding modification amplitude of secret messages in the new embedded domain,the quantization index modulation algorithm is applied to realize the final embedding of secret messages in the original embedded domain.The experimental results show that the algorithm proposed is robust to the three common interpolation attacks including the nearest neighbor interpolation,the bilinear interpolation and the bicubic interpolation.And the average correct extraction rate of embedded messages increases from 50%to over 93% after 0.5 times-fold scaling attack using the bicubic interpolation method,compared with the classical steganography algorithm S-UNIWARD.Also the algorithm proposed has higher detection resistance than the original watermarking algorithm based on quantization index modulation.

MODIFIED QUANTIZATION INDEX MODULATION WATERMARKING ADAPTIVE TO CONTRAST MASKING THRESHOLDS

In this paper,we suggest an adaptive watermarking method to improve both transparence and robustness of quantization index modulation(QIM) scheme. Instead of a fixed quantization step-size,we apply a step-size adapted to image content in each 8×8 block to make a balance of robust extraction and transparent embedding.The modified step-size is determined by contrast masking thresholds of Watson’s perceptual model.From a normalized crossed-correlation value between the original watermark and the detected watermark,we could observe that our method is robust to attacks of additive white Gaussian noise(AWGN),Salt and Pepper noise and Joint Photographic Experts Group(JPEG) compression than the original QIM.By taking into account the contrast insensitivity and visible thresholds of human visual system,the suggested improvement achieves a maximum embedding strength and an appropriate quantization step-size which is consistent with local values of a host signal.

Robust Quantzation Index Modulation VIA Adaptive Watermarking

In this paper,we suggest an adaptive watermarkingmethod to improve both transparence and robustnessof quantization index modulation(QIM)scheme.Instead of a fixed quantization step-size,we apply astep-size adapted to image content in each 8×8block to make a balance of robust extraction andtransparent embedding.The modified step-size isdetermined by contrast masking thresholds ofWatson’s perceptual model.From a normalizedcrossed-correlation value between the original watermarkand the detected watermark,we could observethat our method is robust to attacks of additivewhite Gaussian noise(AWGN),Salt and Peppernoise and Joint Photographic Experts Group(JPEG)compression than the original QIM.By taking intoaccount the contrast insensitivity and visible thresholdsof human visual system,the suggested improvementachieves a maximum embedding strength andan appropriate quantization step-size which is consistentwith local values of a host signal.

Detection of quantization index modulation steganography in G.723.1 bit stream based on quantization index sequence analysis

This paper presents a method to detect the quantization index modulation(QIM) steganography in G.723.1 bit stream.We show that the distribution of each quantization index(codeword) in the quantization index sequence has unbalanced and correlated characteristics.We present the designs of statistical models to extract the quantitative feature vectors of these characteristics.Combining the extracted vectors with the support vector machine,we build the classifier for detecting the QIM steganography in G.723.1 bit stream.The experiment shows that the method has far better performance than the existing blind detection method which extracts the feature vector in an uncompressed domain.The recall and precision of our method are all more than 90% even for a compressed bit stream duration as low as 3.6 s.

A robust watermarking algorithm based on QR factorization and DCT using quantization index modulation technique

We propose a robust digital watermarking algorithm for copyright protection.A stable feature is obtained by utilizing QR factorization and discrete cosine transform(DCT) techniques,and a meaningful watermark image is embedded into an image by modifying the stable feature with a quantization index modulation(QIM) method.The combination of QR factorization,DCT,and QIM techniques guarantees the robustness of the algorithm.Furthermore,an embedding location selection method is exploited to select blocks with small modifications as the embedding locations.This can minimize the embedding distortion and greatly improve the imperceptibility of our scheme.Several standard images were tested and the experimental results were compared with those of other published schemes.The results demonstrate that our proposed scheme can achieve not only better imperceptibility,but also stronger robustness against common signal processing operations and lossy compressions,such as filtering,noise addition,scaling,sharpening,rotation,cropping,and JPEG/JPEG2000 compression.

基于QIM的数字图像盲水印算法

提出了一种DCT域量化索引调制水印算法.水印嵌入在经过像素置换的相邻图像块DCT系数的差值上,根据二值水印的信息位对该差值进行正/负调制,从而实现水印的嵌入.为了平衡不可见性和鲁棒性的要求,根据人类视觉系统的掩蔽特性及图像局部特征对不同嵌入点的嵌入强度进行自适应调整,在确保视觉质量的前提下,得到良好的水印性能.实验结果显示该算法对各种常见图像处理具有良好的鲁棒性.

基于DMWT和QIMM的图像水印算法

利用多尺度分析的思想,对原始图像进行重复行信号预滤波,把标量小波变换扩展到多小波变换后选取变换出来的低频子带进行水印嵌入.为了保证水印信息的安全性,对水印进行加密置乱处理.然后结合量化索引模数调制(QIMM)的优越性能,根据水印的信息不同选择不同的子块进行嵌入并实现了水印的盲提取.实验证明,算法具有良好的视觉性和鲁棒性,并大大扩展了水印的容量.

针对QIM信息隐藏的高效盲检测算法

提出一种基于频谱分析和神经网络分类的盲检测算法,该算法不仅较准确地判断出图像中是否存在隐藏信息,而且可以确定信息隐藏的位置。针对基于QIM方法的信息隐藏,检测时所使用的特征量分别从DCT域和小波域中提取。使用标准图像集所做的实验结果验证了该算法的有效性。

针对音频抖动调制QIM隐写的盲检测

分析了抖动调制(DM)QIM隐写生成的携密音频的特征,利用携密音频段间变换域系数差的绝对值绘制直方图,根据该直方图中存在固定间隔跳跃点的特征,提出了一种盲检测算法。实验验证了该检测算法对音频的抖动调制隐写和简单QIM隐写都有效果。

QIM digital watermarkingbased on LDPC code and messagepassingunder scalingattacks

Watermarking system based on quantization index modulation （QIM） is increasingly popular in high payload applications,but it is inherently fragile against amplitude scaling attacks.In order to resist desynchronization attacks of QIM digital watermarking,a low density parity check （LDPC） code-aided QIM watermarking algorithm is proposed,and the performance of QIM watermarking system can be improved by incorporating LDPC code with message passing estimation/detection framework.Using the theory of iterative estimation and decoding,the watermark signal is decoded by the proposed algorithm through iterative estimation of amplitude scaling parameters and decoding of watermark.The performance of the proposed algorithm is closer to the dirty paper Shannon limit than that of repetition code aided algorithm when the algorithm is attacked by the additive white Gaussian noise.For constant amplitude scaling attacks,the proposed algorithm can obtain the accurate estimation of amplitude scaling parameters.The simulation result shows that the algorithm can obtain similar performance compared to the algorithm without desynchronization.

面向多级分发的矢量地理数据数字指纹算法

矢量地理数据在实际使用过程中通常经过多次分发,已有数字指纹算法多基于单次分发设计,仅能追踪单级分发下的数据泄露,难以追踪整个流通链条。该文提出一种面向多级分发的矢量地理数据数字指纹算法。首先,对矢量地理数据的顶点坐标进行归一化处理;然后,将归一化值的高位与分发级数建立哈希映射,将顶点划分为若干互不重叠的集合;最后,将各级指纹通过QIM方法分别嵌入划分所得的各个顶点集合中。其中,多级指纹编码采用级联码,外码为I码,内码为GD-PBIBD码。仿真实验表明,该算法对缩放、平移、增删点、裁剪等攻击具有较好的鲁棒性,且可有效抵抗常见的线性指纹攻击,准确地追踪到叛逆用户。该算法可用于矢量地理数据多级分发中,为版权保护及盗版追踪提供有力支持。

顾及曲线形状的矢量地图数据水印模型

提出一种矢量地图数据水印模型,利用量化索引调制(QIM)思想,基于变长量化步长,将水印信息隐藏于有效表征曲线形状的特征集合中,在保障算法鲁棒性的前提下,很好地顾及了曲线的形状变形。同时,通过数据哈希分组及水印重复嵌入的方式,将水印信息散布到整个数据集。实验结果表明,该算法在水印的不可见性方面有明显改进,并且在抵抗节点攻击、数据化简及地物删除等很具威胁性的水印攻击方面也具有令人满意的鲁棒性。

基于DCT域的增益不变量化的数字图像水印算法

提出一种新的基于离散余弦变换(discrete cosine transform,DCT)域的增益不变量化索引调制的数字图像水印算法。该算法根据DCT域中DC分量的稳健性,将水印信息采用增益不变的量化嵌入DC分量中,并通过最小距离公式进行水印提取。水印被量化嵌入,提取水印信息无需原载体图像,算法能对水印信息盲提取。实验结果表明,与其他数字水印算法相比,算法有较好的透明性,并对JPEG图像压缩、高斯噪声、中值滤波、泊松噪声、椒盐噪声、缩放等常见图像攻击有很强的鲁棒性。

基于贝叶斯网络的压缩语音信息隐藏检测

压缩语音量化索引调制(QIM)信息隐藏方法中,最近邻投影点QIM(NPP-QIM)方法具有较高的嵌入效率和隐蔽性。针对现有的隐写分析方法对NPP-QIM方法检测准确率不高的问题,提出了一种基于贝叶斯推理的检测方法以提高检测准确率。首先,利用矢量量化(VQ)码字(VQ_1、VQ_2、VQ_3)构建了码字时空转移网络(CSTN);接着,以码字转移指数对CSTN进行化简得到隐写敏感码字时空转移网络(SS-CSTN);然后,基于SS-CSTN进一步构建了码字贝叶斯网络(CBN);最后,使用Dirichlet分布作为先验分布学习网络参数,实现对QIM信息隐藏的检测。实验结果表明,在嵌入率为100%、时长为10 s时,与索引分布特征(IDC)方法和梅尔频率倒频系数(DMFCC)方法相比,提出CBN方法的检测准确率分别提高了25个百分点和37个百分点;在时间性能方法,检测一段10 s的语音时间约为21 ms,能够实时检测。

基于能量量化的音频水印算法

数字水印技术被认为是一种版权保护的重要手段得到了广泛的研究和应用。论文提出了一种基于音频段能量量化的时域音频水印技术,嵌入的水印有良好的隐蔽性,检测过程不需要使用原始信号。实验表明算法对MP3压缩、低通滤波、重采样等常见的攻击手段有满意的鲁棒性。论文还进行了能量量化方法检测错误率的理论分析和自适应量化机制的拓展。

基于音频内容的DCT域脆弱水印算法

为了实现音频文件的完整性认证,提出了一种基于内容的脆弱水印算法.对于一维序列,改变其离散余弦变换(DCT)域交流系数不会改变该序列的幅值和.基于这一性质,在音频分帧后,再对每帧分组,计算每组采样点和的绝对值,相加后得到该帧的和,将其作为该帧音频的特征,量化后转换为二进制作为水印;然后,用量化索引调制方法,通过调整每组DCT域的低频系数嵌入水印.实验表明:该算法具有很好的不可感知性;得到的含水印音频的信噪比约为80 dB;算法对添加噪声、重量化、重采样、低通滤波、MP3压缩等操作具有很强的敏感性,并且能够确定替换等恶意篡改的位置.

基于非均匀DCT的量化索引调制隐写

基于量化索引调制(QIM)的隐写技术正日益受到隐写分析的威胁。该文将通常在DCT域隐写的做法改为在非均匀DCT域进行,将参数作为密钥,提出了一种NDCT-QIM图像隐写方法。由于在攻击者猜测的域中,嵌入信号具有扩散性,NDCT-QIM方法不利于隐写分析对隐写特征的检测,分析和实验表明,它能够更好地抵御基于梯度能量、直方图及小波统计特征等常用统计量的隐写分析,增强了隐写的隐蔽性。

基于DWT-SVD压缩量化的数字图像盲水印算法

为了解决奇异值分解(singular value decomposition,SVD)算法提取水印时需要原始载体图像的缺陷,以及量化索引调制(quantization index modulation,QIM)均匀量化不适用于非均匀信号的问题,通过引入μ律压缩技术,提出一种新的基于DWT-SVD压缩量化的数字图像盲水印算法。该算法对载体图像进行分块,对每一分块实施离散小波变换(discrete wavelet transform,DWT),以及对变换后的近似部分系数进行SVD分解,使用μ律压缩函数压缩分解后的最大奇异值,用QIM的方法嵌入二值水印。算法只用到了最大奇异值,可以盲提取水印,消除因传输原始载体图像产生的不安全性,μ律压缩技术也减小了嵌入水印对原始载体图像的扰乱。仿真实验结果表明,该算法保持了较高的透明性,并对高斯噪声、中值滤波、联合图像专家小组(joint photographic experts group,JPEG)压缩、缩放等常见攻击具有更强的鲁棒性。

一种抵抗插值误差的数字水印方法

几何攻击会给数字水印带来同步误差和插值误差,现有的多数抗几何攻击的鲁棒水印方法都把焦点集中在同步误差上,对插值误差的研究甚少。介绍了常见的插值算法并指明了插值误差产生的原因,能够实现最佳的嵌入率、嵌入失真以及鲁棒性之间平衡的QIM(quantization index modulation)水印算法,进而分析了插值误差对QIM算法的影响,在此基础上提出了针对插值误差的逐像素点选择QIM水印算法。实验在纹理程度不同的10幅图像上进行。实验证明,提出的水印算法对插值误差的鲁棒性优于原始的QIM水印算法。