基于离散余弦变换的大容量信息隐藏盲提取算法

基于图像离散余弦变换(DCT)交流系数的拉普拉斯分布模型,提出了一种盲提取数字图像信息隐藏算法。该算法利用一种新颖的数据嵌入规则,调整绝对值较小的DCT系数的正负值,分别用特定DCT系数的正负值来代表1和0。提取隐藏信息的时候不需要载体图像。实验结果表明,该算法具有容量大的特性,适合于隐秘通信的各种应用。     

On the embedding limits of the discrete cosine transform

This paper investigates the embedding capacity limits of high-capacity data hiding in color images based on a locally Adaptive-Region Discrete Cosine Transform (AR-DCT) frequency domain data hiding scheme, and explores the relationship between hiding capacity and image quality. It also compares the embedding capacities of various steganography schemes which have been recently published in the literature. Experimental results confirm that our proposed scheme successfully enhances hiding capacity while maintaining acceptable image quality and concludes that the capacity for our DCT hiding scheme can achieve extremely high bit rates of 20 bits-per-pixel, which is much higher than other DCT-based approaches, as well as other spatial and frequency domain schemes.     

A novel image steganography scheme with high embedding capacity and tunable visual image quality based on a genetic algorithm

Steganography is knowledge and art of hiding secret data into information which is largely used in information security systems. Various methods have been proposed in the literature which most of them are not capable of both preventing visual degradation and providing a large embedding capacity. In this paper, we propose a tunable visual image quality and data lossless method in spatial domain based on a genetic algorithm (GA). The main idea of the proposed technique is modeling the steganography problem as a search and optimization problem. Experimental results, in comparison with other currently popular steganography techniques, demonstrate that the proposed algorithm not only achieves high embedding capacity but also enhances the PSNR of the stego image.     

LSB based non blind predictive edge adaptive image steganography

Image steganography is the art of hiding secret message in grayscale or color images. Easy detection of secret message for any state-of-art image steganography can break the stego system. To prevent the breakdown of the stego system data is embedded in the selected area of an image which reduces the probability of detection. Most of the existing adaptive image steganography techniques achieve low embedding capacity. In this paper a high capacity Predictive Edge Adaptive image steganography technique is proposed where selective area of cover image is predicted using Modified Median Edge Detector (MMED) predictor to embed the binary payload (data). The cover image used to embed the payload is a grayscale image. Experimental results show that the proposed scheme achieves better embedding capacity with minimum level of distortion and higher level of security. The proposed scheme is compared with the existing image steganography schemes. Results show that the proposed scheme achieves better embedding rate with lower level of distortion.     

An adaptive image steganographic scheme based on Noise Visibility Function and an optimal chaotic based encryption method

Steganography is the science of hiding secret message in an appropriate digital multimedia in such a way that the existence of the embedded message should be invisible to anyone apart from the sender or the intended recipient. This paper presents an irreversible scheme for hiding a secret image in the cover image that is able to improve both the visual quality and the security of the stego-image while still providing a large embedding capacity. This is achieved by a hybrid steganography scheme incorporates Noise Visibility Function (NVF) and an optimal chaotic based encryption scheme. In the embedding process, first to reduce the image distortion and to increase the embedding capacity, the payload of each region of the cover image is determined dynamically according to NVF. NVF analyzes the local image properties to identify the complex areas where more secret bits should be embedded. This ensures to maintain a high visual quality of the stego-image as well as a large embedding capacity. Second, the security of the secret image is brought about by an optimal chaotic based encryption scheme to transform the secret image into an encrypted image. Third, the optimal chaotic based encryption scheme is achieved by using a hybrid optimization of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) which is allowing us to find an optimal secret key. The optimal secret key is able to encrypt the secret image so as the rate of changes after embedding process be decreased which results in increasing the quality of the stego-image. In the extracting process, the secret image can be extracted from the stego-image losslessly without referring to the original cover image. The experimental results confirm that the proposed scheme not only has the ability to achieve a good trade-off between the payload and the stego-image quality, but also can resist against the statistics and image processing attacks.     

基于准三维变换的视频隐写算法

结合离散余弦变换(DCT)的能量压缩能力和离散小波变换(DWT)的多分辨率特性,提出一种基于准三维变换的视频隐写算法。该算法利用二维小波变换描述视频序列的帧内信息,通过一维离散余弦变换描述视频序列的帧间信息,从而有效利用视频序列的空间及时间冗余,将秘密信息嵌入在DCT系数的量化过程中,保证了视频序列的稳定性及秘密信息提取的准确性。实验结果表明,该算法具有较好的视觉不可见性与较高的嵌入容量,且可实现秘密信息的盲提取。     

Adaptive Particle Swarm Optimization Data Hiding for High Security Secret Image Sharing

The main aim of this work is to improve the security of data hiding for secret image sharing. The privacy and security of digital information have become a primary concern nowadays due to the enormous usage of digital technology. The security and the privacy of users’ images are ensured through reversible data hiding techniques. The efficiency of the existing data hiding techniques did not provide optimum performance with multiple end nodes. These issues are solved by using Separable Data Hiding and Adaptive Particle Swarm Optimization (SDHAPSO) algorithm to attain optimal performance. Image encryption, data embedding, data extraction/image recovery are the main phases of the proposed approach. DFT is generally used to extract the transform coefficient matrix from the original image. DFT coefficients are in float format, which assists in transforming the image to integral format using the round function. After obtaining the encrypted image by data-hider, additional data embedding is formulated into high-frequency coefficients. The proposed SDHAPSO is mainly utilized for performance improvement through optimal pixel location selection within the image for secret bits concealment. In addition, the secret data embedding capacity enhancement is focused on image visual quality maintenance. Hence, it is observed from the simulation results that the proposed SDHAPSO technique offers high-level security outcomes with respect to higher PSNR, security level, lesser MSE and higher correlation than existing techniques. Hence, enhanced sensitive information protection is attained, which improves the overall system performance.     

High-capacity steganography: a global-adaptive-region discrete cosine transform approach

An increasing number of spatial and frequency domain data hiding techniques have been proposed to address the relatively low embedding capacities of image-based steganography. These techniques have brought promise of higher embedding capacities, albeit at the expense of lower perceptibility. This work proposes a new discrete cosine transform (DCT) approach for color image steganography and implements a global-adaptive-region (GAR) embedding scheme that allows for extremely high embedding capacities while maintaining enhanced perceptibility. The idea is to adapt the variable region size, used to hide the data, in each DCT block of the cover image to the amount of correlation of the image values in the corresponding block. We will demonstrate how this new technique achieves enhanced hiding capacities and perceptibility compared to other spatial, Fourier, and adaptive-region DCT based steganography schemes.     

基于CL多小波变换和组合位平面理论的秘密信息共享算法

针对信息隐藏算法容量和不可见性与鲁棒性矛盾的特点,提出了一种新的基于Chui-Lian(CL)多小波变换和组合位平面(CBP)理论的数字图像载体预处理算法,并将该算法用于以数字图像为载体的信息隐藏,以实现秘密通信和图像共享。其中,CL多小波变换能够将载体图像划分为4个能量等级不同的最低分辨率子图像,组合位平面理论可将子图像解析为不同的位平面层次,在隐藏秘密信息时,可根据最低分辨率子图和组合位平面的能量等级由高到低分别嵌入鲁棒信息、秘密信息和脆弱信息。实验结果表明,在25%的嵌入率时,与基于离散余弦变换和最低有效位方法的信息隐藏算法（DCT-LSB）、基于离散小波变换和最低有效位方法的信息隐藏算法（DWT-LSB）相比,所提算法针对若干常见攻击的鲁棒性有一定程度提升,峰值信噪比（PSNR）分别提高了37.16%和20.00%。     

基于小波域的大容量图像信息隐藏盲提取算法

目前基于变换域的信息隐藏算法面临容量较小,提取时需要原始图像的问题.提出了一种基于小波变换的大容量信息隐藏盲提取算法,该算法结合人类视觉特性(HVS)及隐密信息自身的特征,以三次小波变换后的低频分量作为参照自适应地调整中高频子带系数来实现信息的嵌入.实验结果表明,该算法具有容量大的特点,并实现了隐密信息的盲提取.     

基于方向编码的离散余弦变换域图像隐写算法

提出一种基于方向编码的离散余弦变换(DCT)域图像隐写算法。将秘密图像进行8×8块的离散余弦变换后,采用JPEG标准量化表进行量化,将得到的DCT系数做行程编码,间接提高嵌入容量。同时对载体图像进行8×8块的离散余弦变换,采用改进的量化表进行量化,由此提高嵌入容量和含密图像的质量。通过基于方向编码的嵌入算法将秘密信息嵌入载体图像DCT系数的中低频部分。实验结果证明,该隐写算法嵌入容量大,得到的含密图像视觉质量好,可抵抗 分析攻击。     

一种基于提升小波变换和矩阵编码的音频隐写算法

以提高隐秘信息嵌入量与隐蔽性为主要目的,利用人耳听觉系统（HAS）的掩蔽效应,提出一种结合提升小波变换和矩阵编码的嵌入隐秘信息的音频隐写算法。该算法利用MPEG I心理声学模型1来控制嵌入帧,选用宿主音频提升小波变换的中低频系数,利用能够大幅提高嵌入效率、减小修改比例的矩阵编码来实现隐秘信息的嵌入。经实验仿真证明,该算法不仅具有很好的隐蔽性和嵌入容量,还兼顾了鲁棒性,对于加噪、滤波、重采样、MP3压缩、同步攻击等常见操作具有较强的抵抗力。同时,该算法能够实现盲检测。     

A new steganography algorithm using polar decomposition

Nowadays, the security of communication becomes very important with the rapid development of network technology. So, the transmission and distribution of the several digital information must be protected and secured against other users. Many steganography techniques have been proposed for embedding secret digital data in other digital data. In this article, we propose a new steganography algorithm based on a linear algebraic tool that is the polar decomposition (PD) for hiding secret data in an image. A host image is selected and divided into blocks of size 2 × 2, a PD is applied on each block, and the secret data are embedded in suitable blocks. Experimental results show that our proposed algorithm gives a higher hiding capacity, achieves good imperceptibility, and also provides a high degree of security against common types of attacks such as compression attack with quality 10%, gamma correction attack, and impulse noise attack.     

减小H.264帧间漂移失真的鲁棒性视频隐写算法

针对H.264/AVC （Advanced Video Coding）视频信息隐藏过程中产生的不可感知性、嵌入容量、鲁棒性三方面不平衡的问题,提出一种通过选取不同优先级顺序的DCT （Discrete Cosine Transform）系数集合实现嵌入,进而减少帧间漂移失真的信息隐藏算法.首先对秘密信息M进行卷积编码,得到编码后的信息,以此提高视频的鲁棒性;然后通过分析帧间漂移失真产生的原因,计算出不同DCT系数优先级顺序的分类集合,优先在失真小的系数集合中嵌入数据从而减小帧间漂移失真;最后根据预先定义的嵌入规则,将嵌入在所选择4×4亮度块的DCT系数集合中,提高嵌入容量.最终在解码端能够正确提取秘密信息同时恢复原始信息.实验结果表明,本文提出的算法能在很好的保证视频质量的前提下,增加视频的嵌入容量,提高鲁棒性.     

Using contourlet transform and cover selection for secure steganography

In this paper, we present a new adaptive contourlet-based steganography method that hides secret data in a specific or automatically selected cover image. Our proposed steganography method primarily decomposes the cover image by contourlet transform. Then, every bit of secret data is embedded by increasing or decreasing the value of one coefficient in a block of a contourlet subband. Contourlet coefficients are manipulated relative to their magnitudes to hide the secret data adaptively. In addition to proposing contourlet-based steganography method, this work investigates the effect of cover selection on steganography embedding and steganalysis results. We demonstrate, through the experiments, that choosing suitable cover image by a proper selection measure could help the steganographer reduce detectability of stego images. The proposed technique is examined with some state-of-the-art steganalysis methods, and the results illustrate that an image can successfully hide secret data with average embedding capacity of 0.02 bits per pixel in a random selected cover image. Cover selection improves the embedding capacity up to 0.06 bits per pixel. Several experiments and comparative studies are performed to show the effectiveness of the proposed technique in enhancing the security of stego images, as well as to demonstrate its gain over the previous approaches in literature.     

基于间隔控制的信息隐藏算法

提出一种在图像离散余弦变换（DCT）域内的信息隐藏算法。为了在基本保证隐秘图像视觉质量的前提下有效提高载体图像的信息隐藏量,该方法使用随机序列进行间隔控制,选择信息嵌入位,把随机序列的种子看成密钥,通过比较变换后的2个DCT系数完成信息的隐藏。试验结果表明,该算法可以兼顾秘密信息隐藏的不可见性和鲁棒性,密钥空间大,能够实现自适应隐藏和提取信息的盲检测。     

Adaptive image data hiding using transformation and error replacement

Watermarking is popular method for effective copyright protection of digital data. The invisible image watermarking is a type of watermarking which is used to conceal secret information in a cover image. In any watermarking system, there is a trade-off between imperceptibility and payload of the data to be hidden in the cover medium. Therefore, only a limited amount of data can be concealed in the cover image while watermark remain imperceptible. This paper proposes a new method of adaptive blind digital image data hiding in Discrete Cosine Transform (DCT) domain using Minimum Error Lease Significant Bit Replacement (MELSBR) method and Genetic Algorithm (GA). In the proposed method, the secret image is embedded into the DCT transformed cover image. Initially, the host and the secret image both are partitioned into equal sized blocks. Then for each secret image block, host image block is intelligently selected through GA and is embedded using MELSBR method. GA helps in identifying the target cover image blocks such that with the LSB embedding, both visual quality of the cover image and imperceptibility of the secret image remain least affected. In watermark extraction process, the watermarked image is decomposed into equal sized blocks and then using the Jigsaw Puzzle Solver (JPS) the secret image is reconstructed. In spite of doubling the payload of the data to hide, the experimental results have shown better imperceptibility and robustness results of the proposed method as compared to the current approaches in this domain.     

基于人类视觉系统的非抽样Contourlet变换域图像隐写算法

为提高图像信息隐藏的容量和隐蔽性,对比分析了非抽样Contourlet变换(NSCT)和Contourlet变换各自的优缺点和适用范围,提出了一种基于NSCT和人类视觉系统(HVS)的图像隐写方案。通过对人眼的视觉掩蔽效应进行建模,在NSCT分解的最精细尺度的各方向子带中,对不同系数分别嵌入不同的秘密信息量。仿真实验表明,新的算法相比小波域中的隐写方案,隐写的嵌入量至少提高了70000b,峰值信噪比(PSNR)提高约4dB,较好地兼顾了隐写在不可见性和嵌入容量上的要求,较小波域中的隐写方案具有更好的应用前景。     

Current status and key issues in image steganography: A survey

Steganography and steganalysis are the prominent research fields in information hiding paradigm. Steganography is the science of invisible communication while steganalysis is the detection of steganography. Steganography means “covered writing” that hides the existence of the message itself. Digital steganography provides potential for private and secure communication that has become the necessity of most of the applications in today’s world. Various multimedia carriers such as audio, text, video, image can act as cover media to carry secret information. In this paper, we have focused only on image steganography. This article provides a review of fundamental concepts, evaluation measures and security aspects of steganography system, various spatial and transform domain embedding schemes. In addition, image quality metrics that can be used for evaluation of stego images and cover selection measures that provide additional security to embedding scheme are also highlighted. Current research trends and directions to improve on existing methods are suggested.     

一种基于关系和量化的强鲁棒性盲水印算法

盲水印提取时不需要参考原始载体图像,在信息隐藏、版权保护等方面具有更广泛的应用前景。提出的盲水印算法在分块离散余弦变换（DCT）和离散小波变换（DWT）的基础上,利用关系双方DCT系数和DWT系数在受到攻击时具有相同变化趋势的特点,采用关系嵌入和量化嵌入的自适应选择嵌入策略,较大幅度地提高了盲水印提取的鲁棒性。同时在量化嵌入中采用抖动调制,实现了水印透明性和鲁棒性调节的便捷性。大量仿真实验结果表明该算法对噪声干扰、低通滤波、JPEG压缩、对比度增强等攻击有很好的鲁棒性和透明性。