安全的密文域图像隐写术

基于同态加密和双层隐写编码,该文提出一种安全的密文域图像隐写术,其可以达到传统明文隐写术的容量,并且在密文域和明文域均能有效抵抗隐写检测分析。首先结合自适应隐写术和湿纸编码技术,提出一种明文域双层隐写算法;其次,修正一种全同态加密算法,对载密图像进行加密;最后,在密文域上提取嵌入的信息。理论分析和实验结果表明:在加密/隐写密钥同时泄露、加密密钥泄露和密钥未泄露条件下,算法均具有较高的安全性。     

一种基于差分进化的鲁棒音频隐写算法

音频隐写是将秘密信息隐藏到音频载体中,已成为信息隐藏领域的一个研究热点。已有研究大多聚焦最小化隐写失真,却以牺牲隐写容量为代价,且往往被一些常规信号攻击后难以正确提取秘密信息。为此,基于扩频技术,首先,分析了隐写参数（分段隐写强度和分段隐写容量）与不可感知性和鲁棒性的关系,并构建了一种以分段隐写强度、分段隐写容量为自变量,以不可感知性和隐写容量为优化目标,以信噪比为约束条件的音频隐写多目标优化模型;然后,提出了一种基于差分进化的鲁棒音频隐写算法,设计了相应的编码、适应度函数、交叉和变异算子。对比实验结果表明,所提隐写算法能够在保证不可感知性和抗隐写分析能力的前提下达到更好的鲁棒性,可以有效抵御一些常规信号处理攻击。     

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。     

隐写术CPT的等价密钥分析

证明了二值图像隐写算法CPT的等价密钥量为2^mn-r.把CPT算法看成一个特殊的分组密码,利用差分分析给出了一个求等价密钥的快速算法,该算法需要mn对明密文,时间复杂度为O(2^r).     

数字图像隐写容量的博弈分析

提出了一种基于数字图像的新的隐写信道模型.在该模型中,考虑隐写分析器的作用和载体与隐秘体的相似性,引入错误概率和检测率作为失真约束条件.运用博弈论,把隐写过程看成编解码方与攻击方的博弈,给出了隐写博弈的双方在不同失真约束条件下的隐写容量,并对容量结果进行了分析.     

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．     

纠错编码在隐蔽通信上的应用

隐写术是一种隐蔽通信技术。隐写术的目的是避免对传送被隐藏消息的行为产生怀疑。分析了隐写系统和隐写分析的基本原理,提出了一种新的隐写载体—纠错编码。建立了一个基于纠错码的隐写系统,提出了一个新的基于线性分组码的隐写算法,并分析了它的可靠性和安全性。     

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。     

基于卷积神经网络的网络隐写分析方法研究

针对现有网络隐写分析算法特征提取难度大、算法适用范围单一的问题,文章提出了一种基于卷积神经网络的网络隐写分析方法。对网络数据流进行预处理,将所有数据包处理成大小相同的矩阵,最大限度地保留数据特征完整性;使用异构卷积进行特征提取,减少模型计算量及参数数量,加快模型收敛速度;取消池化层,提高模型训练效率。与传统网络隐写分析方法相比,模型能够自动提取数据特征,识别多种网络隐写算法。     

基于图像像素划分的主动隐写分析

隐写分析的研究主要集中于隐写检测,而对主动隐写分析研究的较少。该文从隐写检测角度出发,将图像像素划分为不同类点,通过对信息嵌入、最低位平面置反带来的各类点频次变化的分析,提出一种针对空域图像LSB (Least Significant Bit) 替换隐写术的主动隐写分析方法,解决了主动隐写分析中的密钥恢复问题。所提出的方法物理意义直观,实现简单。实验结果表明,该方法在一定嵌入率范围内均可成功恢复隐写密钥。     

Secure steganography based on binary particle swarm optimization

The objective of steganography is to hide message securely in cover objects for secret communication. How to design a secure steganographic algorithm is still major challenge in this research field. In this letter, developing secure steganography is formulated as solving a constrained IP (Integer Programming) problem, which takes the relative entropy of cover and stego distributions as the objective function. Furthermore, a novel method is introduced based on BPSO (Binary Particle Swarm Optimization) for achieving the optimal solution of this programming problem. Experimental results show that the proposed method can achieve excellent performance on preserving neighboring co-occurrence features for JPEG steganography.     

基于大数据环境的多模态信息隐藏新体系

信息隐藏研究经过数十年的发展,在隐写术和隐写检测方面都积累了大量成果,但是信息隐藏的应用目前仍局限于实验室研究,聚焦于发现与抗发现的对抗,距实际应用仍有一定的距离.论文在对当前信息隐藏研究深入分析的基础上,借鉴密码学思想,提出建立适应于当前大数据环境,算法可变、修改模式可控的抗取证信息隐藏系统;通过全面整合信息隐藏算法和嵌入修改模式,构建多模态信息隐藏技术空间,实现用户通过输入密钥参与信息隐藏处理控制的全新研究思路和应用方式.论文通过理论分析和实验初步验证该系统的有效性和安全性.     

基于图像高阶MARKOV链模型的扩频隐写分析

 扩频隐写分析是信息隐藏研究领域的一个重要方面.文章提出基于高阶Markov链的数字图像统计分布模型,在对常用图像扫描方法构成高阶Markov链的效果进行比较后,采用Hilbert扫描方式构建数字图像n阶Markov链模型,进而提出度量数字图像隐写统计安全性的n阶Markov链测度,并证明其有界.最后文章通过研究扩频隐写对高阶Markov链模型经验矩阵的影响,利用该模型提取图像统计特征,并使用支持向量机对几种常用图像扩频隐写方法进行分析.实验说明文章所提方法对扩频隐写分析效果良好,且随着模型阶数提高,分析准确率也随之提高.     

A Model‐Based Image Steganography Method Using Watson's Visual Model

This paper presents a model‐based image steganography method based on Watson's visual model. Model‐based steganography assumes a model for cover image statistics. This approach, however, has some weaknesses, including perceptual detectability. We propose to use Watson's visual model to improve perceptual undetectability of model‐based steganography. The proposed method prevents visually perceptible changes during embedding. First, the maximum acceptable change in each discrete cosine transform coefficient is extracted based on Watson's visual model. Then, a model is fitted to a low‐precision histogram of such coefficients and the message bits are encoded to this model. Finally, the encoded message bits are embedded in those coefficients whose maximum possible changes are visually imperceptible. Experimental results show that changes resulting from the proposed method are perceptually undetectable, whereas model‐based steganography retains perceptually detectable changes. This perceptual undetectability is achieved while the perceptual quality — based on the structural similarity measure — and the security — based on two steganalysis methods — do not show any significant changes.     

A novel haze image steganography method via cover-source switching

In realistic outdoor scenarios, image sensors tend to suffer from various weather conditions (e.g., haze, rain, etc.),which make the images of the same scene taken at different times may be different. Therefore, one should be able to securely embed secret messages into these images by making use of the variations of the weather effects. Inspired by some recent natural steganography algorithms, this paper presents a novel haze image steganography method, which embeds messages through adjusting the weather effects of an input haze image, making it resemble the same image captured under another weather condition. The proposed steganography method consists of three parts: (1) model parameter estimation of the input haze image, (2) haze effects adjustment according to the atmospheric scattering model, (3) message embedding using the floating-point adjusted haze image. 10,000 haze images captured under different haze conditions in various scenarios were used to test the proposed steganography algorithm. The experimental results show that the proposed steganography algorithm is more secure than S-UNIWARD and HILL for steganalyzers who only have raw haze images.     

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.     

Spread spectrum image steganography

We present a new method of digital steganography, entitled spread spectrum image steganography (SSIS). Steganography, which means "covered writing" in Greek, is the science of communicating in a hidden manner. Following a discussion of steganographic communication theory and review of existing techniques, the new method, SSIS, is introduced. This system hides and recovers a message of substantial length within digital imagery while maintaining the original image size and dynamic range. The hidden message can be recovered using appropriate keys without any knowledge of the original image. Image restoration, error-control coding, and techniques similar to spread spectrum are described, and the performance of the system is illustrated. A message embedded by this method can be in the form of text, imagery, or any other digital signal. Applications for such a data-hiding scheme include in-band captioning, covert communication, image tamperproofing, authentication, embedded control, and revision tracking.     

Steganalysis for palette-based images using generalized difference image and color correlogram

In this paper, we attempt to propose a novel blind steganalysis algorithm for palette-based images. First, the generalized difference images between adjacent pixels were constructed, and then the moments of characteristic functions of difference images' histograms were extracted as features. Second, in order to measure the dependencies of neighboring colors, color correlogram technique is used to capture the global distribution of local spatial correlation of colors. The center of mass of the characteristic function of color correlogram and the absolute moments of autocorrelogram were extracted. Total of 13 dimension features were classified with machine learning technique. Number of experiments on several existing GIF steganography algorithms indicated that the proposed scheme is effective and gets good performance, especially when the embedding rate is not less than 20%. Experimental results also show that the average accuracy of our proposed scheme for different GIF steganography algorithms outperforms Lyu's algorithm more than 20%. It also showed that the proposed scheme achieved similar performance with Fridrich's scheme and higher accuracies comparing to Du's algorithm and biologically inspired features.