一种基于LSB的易碎性数字盲水印算法

提出了一种基于LSB的易碎性数字盲水印算法.水印由m序列确定的嵌入像素LSB清零后的原始图像CRC-32值、有意义的二值图像及其CRC-32值组成,嵌入到由m序列确定的像素LSB中,有效地解决了信息隐藏、盲水印提取和篡改检测等关键问题.试验结果表明,该算法能够满足数字档案资料版权保护和篡改鉴真的要求,具有实用价值.     

基于椭圆曲线密码体制信息隐藏设计与实现

文中利用椭圆曲线密码体制密钥短，安全性高的特点，并结合改进的LSB算法，将加密通信和信息隐藏相结合，提出基于椭圆曲线密码体制与改进的LSB算法的秘密信息隐藏方案。文中对方案的秘密信息嵌入和提取过程都进行了详细阐述。可以根据BMP图像的特点实现是否有秘密信息嵌入的检测，并给出了方案实现的信息隐藏的效果图。     

一种利用游程编码的信息隐藏方法

提出了一种隐藏二值图像的方法。利用游程编码技术对二值图像的无损压缩来减少对掩护载体的像素修改，并通过混沌序列对隐藏的信息序列进行加密。实验结果表明，相对于传统的LSB隐藏方法，该算法在一定程度上能抵抗RS检测攻击，其载密图像在视觉上更不容易被察觉，秘密信息的安全性得到了增强。     

数字图像隐秘信息的检测与定位算法

提出一个新的针对空域LSB方法在JPEG格式图像隐藏信息的检测-9定位算法。首先检测图像的JPEG压缩历史，并提取JPEG图像的质量因子。根据含秘图像和质量因子推导出原始图像的像素信息．比较含秘图像与原始图像的差异就可识别出隐秘信息的嵌入位置，并由此估算出隐密信息的嵌入量。它可检测多种LSB信息隐藏软件，包括Hide＆Seek，S-Tools4，Steganos，EZStego等，算法的效果通过对S-Tools4的检测得到证明。     

VQ域信息隐藏检测算法

随着信息隐藏技术的发展，基于矢量量化（VQ）的信息隐藏的方法逐渐增多．本文提出了一种VQ域隐藏信息检测方法，首先通过全局搜索在已经解码的无压缩图像中恢复量化码书，然后应用聚类分析的思想将矢量空间中相近的码字归类以判断是否存在隐藏信息，最后根据各个码字的出现概率估计嵌入信息的长度．实验表明，本文提出的算法对隐藏信息的存在性有很高的识别率，对信息量的估计也比较准确．     

多级秘密信息隐藏方法

针对普通的一级秘密信息隐藏的方法具有安全性低,视觉效果差的问题,本文提出了一种多级别信息隐藏的方法.该方法使一级秘密信息在一级密钥作用下成为宿主图像,提高了信息隐藏的安全性,再将宿主图像分成3×3的图像块,在二级密钥的控制下成功将二级秘密信息嵌入.采用图像置乱和LSB算法的结合方法,并在两级秘密信息的作用下,使得载密图...     

基于 RSA 与 LSB 算法的信息隐藏

信息隐藏技术将特定信息嵌入数字化宿主信息中,由于宿主信息呈现变化不大,不会引起监控者的注意和重视,从而减少了被攻击的可能性。为了提高信息隐藏效率与在非授权情况下提取信息的难度,提出将信息加密后进行隐藏,具有更高的安全性。在信息隐藏前对敏感信息进行了信息分割、RSA加密预处理;将控制信息也嵌入到BMP文件的图像数据区;实现了改进的LSB算法,并通过实验进行了验证。     

一种改进的最低有效位信息隐藏算法

针对空间域的最低有效位(LSB)算法鲁棒性低且抗攻击能力弱的特点,提出一种改进的算法。首先,用Arnold变换对秘密信息进行置乱预处理,使真实信息变成乱码;然后,在信息嵌入过程中,调整载体信息最低两个比特位,使它所表示那一个比特位与秘密信息的比特位相一致,避免了传统LSB算法直接在载体信息最低位上嵌入秘密信息;最后,用逻辑运算实现信息隐藏,故信息的提取只需要简单的运算。实验表明,改进后的算法有效增强其鲁棒性,能有效抵抗加噪、滤波和剪切等非法攻击。     

基于HSB与LSB的半脆弱水印算法

提出了一种能够精确定位并能恢复原图像的半脆弱数字水印算法。本算法利用LSB(最低比特位)所含水印信息大容量的特点,由于在图像篡改和水印攻击情况下HSB(最高比特位)具有相对稳定性,故利用HSB作为水印信息,利用一种新的置乱算法产生水印嵌入位置,结合混沌序列,修改该位置图像像素的LSB,完成水印的嵌入调制。实验结果表明,该算法不仅可对图像内容的恶意篡改进行精确地检测与定位,而且能够大致恢复出被篡改的原图像信息,并对原图质量的影响非常小。     

传统LSB图像隐藏算法的优化研究

信息隐藏技术是信息安全领域的重要组成部分。针对只选最低位的LSB算法会导致隐藏信息量不够大的缺点,提出了优化的LSB算法。该方法在传统的LSB图像隐藏算法的基础上,结合遗传算法,实现秘密信息的自适应嵌入。理论分析和实验表明,这种优化算法不仅具有算法简单、隐蔽性好的特点,还具有隐藏信息容量大、均方根误差小等优点。     

Detecting LSB steganography in color, and gray-scale images

We describe a reliable and accurate method for detecting least significant bit (LSB) nonsequential embedding in digital images. The secret message length is derived by inspecting the lossless capacity in the LSB and shifted LSB plane. An upper bound of 0.005 bits per pixel was experimentally determined for safe LSB embedding     

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     

Dual Image Reversible Data Hiding by Modifying Least-Significant-Bit Matching Revisited Rules

The concept of dual image reversible data hiding (DIRDH) is the technique that can produce two camouflage images after embedding secret data into one original image. Moreover, not only can the secret data be extracted from two camouflage images but also the original image can be recovered. To achieve high image quality, Lu et al.'s method applied least-significant-bit (LSB) matching revisited to DIRDH. In order to further improve the image quality, the proposed method modifies LSB matching revisited rules and applies them to DIRDH. According to the experimental results, the image quality of the proposed method is better than that of Lu et al.'s method.     

Image steganographic scheme based on pixel-value differencing and LSB replacement methods

In order to improve the capacity of the hidden secret data and to provide an imperceptible stego-image quality, a novel steganographic method based on least-significant-bit (LSB) replacement and pixel-value differencing (PVD) method is presented. First, a different value from two consecutive pixels by utilising the PVD method is obtained. A small difference value can be located on a smooth area and the large one is located on an edged area. In the smooth areas, the secret data is hidden into the cover image by LSB method while using the PVD method in the edged areas. Because the range width is variable, and the area in which the secret data is concealed by LSB or PVD method are hard to guess, the security level is the same as that of a single using the PVD method of the proposed method. From the experimental results, compared with the PVD method being used alone, the proposed method can hide a much larger information and maintains a good visual quality of stego-image.     

基于Logistic映射与LWT的音频隐写算法

提出了一种基于Logistic序列置乱与小波提升的高层LSB音频隐藏算法。为了增加传输过程的安全性,在前端用Logistic混沌序列对秘密语音进行扰乱。针对传统的LSB鲁棒性差的问题,提出了将秘密语音的小波系数嵌入载体小波系数的第9～12位的算法,该算法的隐藏量为载体语音容量的25％。通过仿真实验证明,该算法透明性好,且可以实现盲提取,将含密载体通过QQ传输之后也可以正确提取秘密语音。     

A Novel High Capacity Reversible Information Hiding Scheme Based on Side-Match Prediction and Shortest Spanning Path

In recent years, information hiding techniques have attracted increased attention owing to the growing demand for the ability to exchange large amounts of information. In addition, hiding information in compressed messages is very practical in improving transmission efficiency and saving large amounts of storage space. However, the damage caused by hiding data in compressed messages reduces image quality more than the damage caused by hiding data in uncompressed messages. Hence, this paper proposes a data hiding scheme based on side-match prediction and declustering techniques for vector quantization (VQ) compressed images. The appropriate side-match prediction not only embeds secret information into the VQ index but also reverses the original compressed index. In addition, the capacity for secret information can be varied adaptively depending on the requirements of different applications. As experimental results indicate, the proposed scheme indeed outperforms previous work in hiding capacity and in the image quality of stego-images.     

基于拉普拉斯算子统计量的LSB替换隐写分析方法

该文基于对图像像素点的拉普拉斯算子统计量的分析,提出了两种新的LSB替换隐写分析方法.首先定义了描述像素点与4-邻域像素均值关系的统计量,进而通过对隐秘信息的嵌入、LSB平面二次嵌入和LSB平面置反带来的变化分析,提出了隐秘信息的检测方法1和隐写嵌入率的准确估计方法2.该文提出的二个方法实际物理意义明显,实现简单.实验结果表明在嵌入率不小于20%时方法2估计准确率优于RS方法.     

一种基于湿纸编码和图匹配理论的直方图保持隐写算法

该文结合隐写码、湿纸码和图匹配理论提出一种具有高嵌入效率的且可保持载体图像一阶直方图的双层嵌入隐写算法.首先构造出一条新的四进制的隐写信道,然后在该信道的LSB(Least Significant Bit)层和次LSB层分别使用二元隐写码和湿纸码嵌入秘密消息,这样即可确定出需要修改的元素,接着构造出一个图,最后使用图论...     

一种基于小波对比度和LSB的密写

为了提供较大的秘密信息嵌入量和保持良好的载密图像质量,依据人眼对变换剧烈及较暗区域均不敏感的视觉特点,提出了一种基于小波对比度和最低比特位替换(LSB)的图像密写方法.该方法先将载体图像分成固定大小的小块,对每一小块进行小波分解后计算小波对比度.然后,根据该块小波对比度绝对值之和确定该块可以嵌入的位平面层数.最后,采用LSB密写技术逐层嵌入秘密信息.实验结果表明,该密写方法能嵌入较多的信息和保持良好的载密图像质量,并且可直接从载密图像中提取秘密信息.