基于PVD隐写术的载体图像的选择研究

设计高性能嵌入算法与选择合适载体图像是提高隐写术性能的两个重要途径.基于像素差值PVD(pixel-value differencing)是一种算法复杂度低,嵌入容量大的高性能隐写算法.本文针对PVD嵌入算法,研究最佳载体选择问题.论文分析与讨论载体图像的复杂度、直方图及其平滑度等载体图像特征值,和相对熵、直方图的改变量等隐写术系统性能参数之间的关系,研究载体图像的特征值对PVD隐写术系统性能的影响,为PVD隐写算法选择最佳的载体图像提供理论依据.实验结果表明,选择直方图曲线连续变化缓慢的图像作为PVD隐写算法的载体图像,能有效提高隐写术系统的不可感知性能.     

一种空域频域结合的图像隐写算法

为了获取较大隐写容量和较好的不可感知性,使用图像空域边缘特点结合人眼视觉感知特性,提出一种空域频域相结合的大容量图像隐写算法,既考虑了图像在空域中的边缘信息,又考虑了图像亮度等因素对嵌入区域的影响。使用对比灵敏度和纹理能量对嵌入区域进行整合,根据容量大小和不可感知程度来选择频域或空域对图像嵌入秘密信息。通过实验表明,该算法在得到了较大的隐写容量的同时也获得了较好的不可感知性。     

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。     

彩色JPEG图像的隐写分析

图像隐写分析的目的是检测图像中隐藏信息的存在性．JPEG图像的广泛使用使其成为一种重要的隐写载体，因而针对JPEG图像的隐写分析受到研究者们的广泛关注．本文基于彩色图像YCbCr颜色空间DCT系数的统计分布模型，提出一种彩色JPEG图像的隐写分析算法．通过计算载体图像和掩密图像DCT系数统计分布之间的鉴别信息，评估常见DCT域隐写术对载体图像DCT系数统计分布的改变．以统计分布模型参数为特征向量，采用支持向量机实现对载体图像和掩密图像的有效分类．实验结果表明，本文算法具有较高的检测率，性能优于使用Faxid所提出的彩色QMF统计量的隐写分析算法．     

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,最后使用图论中匹配算法寻找一种减小失真且保持直方图的修改方式。性能分析和实验结果表明:在嵌入相同长度秘密消息的情况下,新算法的PSNR、嵌入效率和保持一阶直方图效果均优于隐写软件Steghide。     

基于非线性残差的JPEG图像隐写分析

当前JPEG图像隐写分析方法往往只使用线性滤波器生成残差图像,导致残差图像类型过于单一,影响隐写检测性能。鉴于此,提出了基于非线性残差的JPEG图像隐写分析方法。首先,从现有JPEG图像隐写分析方法已有的线性残差图像中选择合适的图像组,对其采用逐像素取小和取大运算,在没有明显增加计算复杂度的情况下,得到非线性残差图像。其次,根据JPEG相位,将非线性残差图像划分为子图像,提取子图像直方图特征。再次,充分考虑非线性运算的影响,设计合适的特征对称合并方法。最后,将合并后的直方图特征拼接形成最终的隐写分析特征。实验结果表明,线性和非线性残差图像相结合能够有效地增加残差图像和隐写分析特征的多样性,从而提升JPEG图像隐写检测性能。     

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。     

结合图像边缘检测和最小误差替换的隐写方案

为了实现大容量、低感知度的数字图像隐写,根据人眼视觉系统对图像边缘变化不敏感的特点,提出一种结合图像多尺度边缘检测和最小误差替换的自适应算法。简单介绍了常用的图像边缘检测算法以及Canny算子,而后通过利用Canny算子检测图像边缘像素。再按一定比例将秘密信息分别嵌入到边缘像素和普通像素中,并对比选用不同嵌入比例时算法的隐写容量和峰值信噪比差异,选定合适的嵌入比例。最后采用最小误差替换方法修正图像峰值信噪比,降低图像失真度,并对比算法针对不同载体时的嵌入容量和峰值信噪比。实验结果表明:以图片"Baboon"作为载体按4∶1嵌入比例隐写秘密信息时,本方案嵌入容量为525 612bit,载秘图像峰值信噪比为41.3dB。该算法不仅隐写容量十分可观,而且失真度小,计算简单,易于实现。     

基于分数基音延迟动态搜索的语音隐写算法

论文提出了一种基于分数基音延迟动态搜索的语音隐写算法.该算法可根据隐藏容量（x比特/子帧）的需要将分数基音延迟候选值集合划分为2x个子集,每个子集代表不同的x比特信息.在闭环基音搜索过程中,可为每个子帧选择既能表示待嵌入隐秘信息且内插后的归一化相关系数最大的分数基音延迟候选值,从而有效降低隐写操作对于原始载体的影响.以目前IP语音系统中广泛使用的自适应多速率语音编码为例,对该算法从隐藏容量、不可感知性及抗检测性三方面进行了性能评估并与相关工作进行了对比分析.实验结果表明,本文提出的隐写算法较之现有基于基音延迟的隐写算法可在确保较高隐写容量的同时达到更好隐写安全性（即更好抗检测能力和不可感知性）.     

基于DCT域的数字图像隐写术分析

在多媒体通信的安全问题上,隐写术起着至关重要的作用。针对隐写术中常用的DCT域数字图像隐写方法,对秘密信息在mother和Lena图像中的隐写效果进行了仿真,研究了秘密信息在图像DCT域中的不同嵌入位置、不同的载体图像进行隐写时,对图像质量所产生的影响。研究表明:将信息嵌入图像的低频部分、选取像素值分布较丰富的图像,有利于提高信息在图像中的隐写效果,增强秘密信息的隐蔽性。     

一种保持直方图特性的JPEG图像掩密算法

传统的JPEG图像掩密算法往往因为改变了载体图像的DCT系数直方图而不能抵抗各种基于直方图的攻击,或者为了矫正直方图而降低了隐藏容量,该文提出一种新的保持直方图特性的算法。该算法在嵌入秘密消息时,动态建立Adjust_info表记录系数直方图被改变的情况,然后根据该表调整系数的变化方向,这样不但可以补偿直方图的改变,而且并不降低隐藏容量。对多幅图像的实验表明,该算法不但能够达到13%的高隐藏容量(压缩因子为75),而且掩密后图像总体DCT系数直方图的平均失真率为0.81%。由改进算法掩密后图像低频DCT系数直方图的最大失真率为3.83%,平均失真率只有1.98%,仅对直方图做了微小的改变,因此可以有效抵御各种直方图攻击,从而为安全掩密提供了可靠保证。     

Enhanced hybrid image security algorithms for high definition images in multiple applications

Protection of multimedia information from different types of attackers has become important for people and governments. A high definition image has a large amount of data, and thus, keeping it secret is difficult. Another challenge that security algorithms must face with respect to high definition images in medical and remote sensing applications is pattern appearances, which results from existing regions with high density in the same color, such as background regions. An encryption and hiding based new hybrid image security systems are proposed in this paper for the purpose of keeping high definition images secret. First, one hiding method and two encryption methods are used in two hybrid algorithms. The new hiding algorithm proposed here starts by applying reordering and scrambling operations to the six Most Significant Bit planes of the secret image, and then, it hides them in an unknown scene cover image using adding or subtracting operations. Second, two different ciphering algorithms are used to encrypt the stego-image to obtain two different hybrid image security systems. The first encryption algorithm is based on binary code decomposition, while the second algorithm is a modification of an advanced encryption standard. After evaluating each hybrid algorithm alone, a comparison between the two hybrid systems is introduced to determine the best system. Several parameters were used for the performance, including the visual scene, histogram analysis, entropy, security analysis, and execution time.

     

Reversible data hiding scheme using reference pixel and multi-layer embedding

This paper presents a lossless data hiding scheme. The proposed scheme is based on the pixel difference histogram shifting to spare space for data hiding. Pixel differences are generated between a reference pixel and its neighbors in a pre-assigned block. After the difference histogram shifting, a large number of data can be embedded into the cover image, and multi-layer embedding is used to improve the hiding capacity. Different from previous works based on histogram shifting the proposed scheme can extract the hidden data and recover the exact original cover image with no extra information except the length of hidden data and the stego-image itself. Experimental results show that the average pure payload among eight commonly used grayscale images is up to 1.08 bits per pixel (bpp) while keeping low distortion.     

An embedding strategy on fusing multiple image features for data hiding in multiple images

Data hiding in multiple images has been a significant research direction in information security. How to reasonably design the embedding strategy to spread the payload among multiple images is still an open issue. In this paper, we propose an embedding strategy on fusing multiple features. We utilize the typical characteristic parameters of gray level co-occurrence matrix, the image entropy and the shape parameter to describe image complexity. Furthermore, we combine with the number of cover images, the number of cover images assigned to steganographer and the size of cover image to estimate the steganographic capacity of each image. The strategy is implemented together with some state-of-the-art single image steganographic algorithms. Experimental results demonstrate that the security performance of the proposed strategy is higher than that of the state-of-the-art embedding strategy against the blind universal pooled steganalysis.     

图像分存中的信息隐藏算法研究

针对现在大多图像信息隐藏算法中存在的隐藏容量小、安全性差的问题,提出了一种基于特定数学原理的载体图像分存隐写算法。首先构建图像分存的隐写模型,其次阐述了Bernstein多项式和Frobenius数问题的性质以及相关定理并提出分存算法,然后将载体图像进行分存变换,最后,给出了隐秘信息的嵌入与提取算法,并进行了分存隐写和...     

Reversible data hiding with automatic contrast enhancement using two-sided histogram expansion

Recently, reversible data hiding (RDH) has emerged into a new class of data hiding methods that enables exact retrieving of both embedded data and cover medium. In the present study, a novel automatic RDH method with contrast enhancement is proposed, in which the data is embedded through two-sided histogram expansion. Two-sided histogram shifting doubles the number of bits embedded at each iteration. Moreover, it preserves the mean brightness of the cover image and prevents it from over enhancement with less calculation. Experimental results on two sets of images show that the proposed method enhances the image contrast at an appropriate level without using a mean brightness controller during data embedding and provides higher information security compared to the existing RDH approaches.     

An entropy minimization histogram mergence scheme and its application in image compression

In this paper, we propose an entropy minimization histogram mergence (EMHM) scheme that can significantly reduce the number of grayscales with nonzero pixel populations (GSNPP) without visible loss to image quality. We proved in theory that the entropy of an image is reduced after histogram mergence and that the reduction in entropy is maximized using our EMHM. The reduction in image entropy is good for entropy encoding considering that the minimum average code word length per source symbol is the entropy of the source signal according to Shannon’s first theorem. Extensive experimental results show that our EMHM can significantly reduce the code length of entropy coding, such as Huffman, Shannon, and arithmetic coding, by over 20% while preserving the image subjective and objective quality very well. Moreover, the performance of some classic lossy image compression techniques, such as the Joint Photographic Experts Group (JPEG), JPEG2000, and Better Portable Graphics (BPG), can be improved by preprocessing images using our EMHM.     

A secure high capacity full-gray-scale-level multi-image information hiding and secret image authentication scheme via Tchebichef moments

The growth of image processing tools and applications has made it easy for multi-media content such as music, audio, and video to be manipulated or forged during transmission over the Internet. Efforts, such as information hiding in steganography, have been unable to secure data transmission and prevent its manipulation. Usage of coding theory, including cryptography, is not full proof in the sense that an unauthorized intruder may inject (tampering) and incorporate unintended data to the messages, which can tamper the transmitted data. There is a need for more transparent message information hiding schemes along with information content verification and authentication, as well as accurate tampering detection. In particular, as it is well known, in many current steganography methods, widely used for image information hiding, there are various technical challenges associated with hiding large amounts of image information in images. Some of these challenges relate to which locations, in a given carrier image, information has to be hidden in order to guarantee transparency of the resulting watermarked images, to the ability to extract hidden information accurately, to the performance of hidden secret information authentication and verification at the receiving end, to the dependency of the hidden information on a given carrier image, to the robustness of information hiding schemes to affine transformations such as rotation, and to the amount of data and number of full-scale images one can embed in a given single image carrier. Additionally, as it is well known, many of the existing stenography methods are based on the Discrete Fourier Transform (DFT), the Discrete Cosine Directors (DCT), or the Discrete Wavelength Transform (DWT) methods, which result in high Bit Error Rate (BER) of the extracted data. In this paper we present a secure high capacity image information hiding scheme where two full separate arbitrary full-scale gray level images (versus binary), one hidden information image and one authentication watermark image are hidden/embedded in the Tchebichef moments of a carrier image with very high imperceptibility. Here the second watermark image is used for identification and content integrity verification and authentication of the hidden secret image. Both the hidden secret hidden image and the authentication watermark image are of the same size as that of a given arbitrary carrier image. In particular, with the cost of computer memory getting lower and the bandwidth of transmission channels getting larger, we show how three different watermarked images, but the same to a naked eye, are produced and transmitted to achieve the desired advantages of high accuracy, security, authentication and verification of the recovered information. To the best of our knowledge, this two-full-scale gray images data hiding and hidden secret image information verification and authentication method is the first attempt of its sort. We show here the robustness of the proposed scheme to affine transformations such as rotation, scaling, and translation, the proposed scheme's high image malicious tampering detection and tampering localization and its high quality extracted recovered and authenticated hidden secret images. Additionally, in order to as much as possible keep the integrity of the received information, when watermarked images are rotated during transmission, a new image rotation estimation and recovery algorithm is presented as part of the proposed information hiding scheme. We show the effect of intended tampering attacks namely, cropping, noise, low-pass and high-pass filtering on the presented scheme. We also show how the extracted information accuracy is generally independent of the carrier image, and we present a mathematical analysis for characterizing the conditions under which transparency of the hidden embedded information is generally achieved for any given arbitrary carrier image. The case of how to extract the hidden information when one or two of the watermarked images is (are) lost is also tackled. Finally, experimental results on real images are presented to illustrate the efficiency and capabilities of the proposed method.     

针对JPEG格式的数字隐写与隐写分析

数字隐写和隐写分析是信息隐藏技术的重要分支。JPEG图像是隐写术最常见的载体,因而研究以JPEG图像为载体的隐写和隐写分析具有重要意义。剖析了JPEG文件结构,提出了基于JPEG格式的隐写方案;并针对该方案提出了相应的隐写分析方案;然后通过大量统计,建立了两个数据库,并最终构建了一个准实时隐藏信息提取系统。该系统从5万幅互联网上的JPEG图像提出了信息,并有效攻击了11种互联网上的隐写软件。