嵌入率可调和低修改率的二值图像密写算法

为了提供大而可调的二值图像信息隐藏容量和保持载密二值图像良好的视觉质量,提出一种基于分块和矩阵编码的二值图像信息隐藏算法.将二值图像划分为互不相交的2×2的图像子块,随机选择黑白相间的边缘子块作为可嵌子块,应用(1,n,k)矩阵编码实现最多只改变n块可嵌子块中一块的1个像素即可嵌入k比特信息,以及修改像素的规则.选择不同的矩阵编码方案,可以得到不同的嵌入率和像素修改率.理论分析和实验结果表明,本文算法具有信息嵌入量大,效率高,修改率低,安全性好;其信息嵌入率选择具有高度弹性,可以根据实际要求选择在嵌入率和载密图像质量都很理想的密写方案.     

基于图像复杂度的隐写方法研究*

为了提供较大的隐写容量和保持良好的载密图像质量,依据人眼对纹理、边界和黑暗区域变化敏感性弱的视觉特点,结合小波变换提出了一种图像复杂度描述方法,将图像小块分为纹理、边界、黑暗和平滑四个不同类别,利用模函数设计隐写算法,在不同区域嵌入不同量的信息。实验结果表明,新的复杂度描述方法能准确区分不同类型的小块,隐写算法在提高嵌入容量的同时保持了较好的视觉质量。     

一种基于SOM和HVS的密写方法

为了提供较大的秘密信息嵌入量和保持较好的载密图像质量,提出了一种基于自组织特征映射神经网络和人眼视觉特性的图像密写。该密写方法将对比度和纹理敏感度作为特征向量,并通过自组织特征映射神经网络将像素分为视觉敏感类与视觉不敏感类,将较多秘密信息嵌入属于视觉不敏感类的像素,而将较少秘密信息嵌入属于视觉敏感类的像素。实验结果表明,与SOC算法相比,该算法有更大的嵌入量,并保持了良好的载密图像质量。     

优化参数化二元模映射信息隐藏

目的 针对目前信息隐藏的嵌入和提取函数为固定表达式,存在容易被隐写分析和非法提取信息的安全隐患,以及基于模函数的隐写研究现状,提出信息隐藏参数化设计思想、优化参数化二元模映射隐写算法。方法 首先提出信息隐藏参数化设计定义和分析参数化信息隐藏算法的安全性,然后提出优化参数化二元模映射隐写算法。优化参数化二元模映射隐写算法将两个像素值优化组合后的模运算结果映射到一位n²进制信息,从而实现信息隐藏。结果 优化参数化二元模映射隐写算法的密钥空间大,载密图像均方差小于或等于同类算法。结论 信息隐藏参数化设计可以有效提高信息隐藏算法的抗隐写分析能力和抗信息提取能力;优化参数化二元模映射隐写算法与同类算法相比,具有更好的载密图像视觉质量和安全性。     

基于FCM和HVS的密写方法

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,该文提出一种基于模糊C均值聚类和人眼视觉特性的图像密写。该密写方法将对比度和梯度敏感度作为特征向量,并通过模糊C均值聚类将像素分为视觉敏感类与视觉不敏感类,将较多秘密信息嵌入属于视觉不敏感类的像素,而将较少秘密信息嵌入属于视觉敏感类的像素。实验结果表明,与四边匹配算法相比,该算法有更大的嵌入量并保持了良好的载密图像质量。     

基于HVS和SOM的小波域隐写

为了提供较大的秘密信息嵌入量并保持良好的载密图像质量,提出一种基于SOM(自组织特征映射神经网络)和HVS(人眼视觉特性)的小波域图像隐写.该方法先将载体图像分成固定大小的小块,以小波对比度之和以及小波系数方差作为特征量.然后,利用SOM将小块分为三类.最后,采用模算子隐写将秘密信息嵌入到小波系数中.实验结果表明,与WHS算法相比,该算法有更大的嵌入量并保持了良好的载密图像质量.     

基于小波对比度和模函数的安全密写算法

针对图像隐写中大容量、高保真度和安全性问题,依据人眼对变换剧烈及较暗区域均不敏感的视觉特点,结合模函数周期性运算,提出一种基于小波对比度和模函数运算的高保真图像隐写算法。该方法首先将载体图像按固定大小分块并计算其小波对比度,然后依据小波对比度确定各块嵌入深度,最后采用模函数运算嵌入秘密信息。实验结果表明,该方法能嵌入较多信息和保持良好的载密图像质量。     

基于视觉感知与菱形编码的图像隐写算法

为提供较大的隐写容量和保持良好的载密图像质量,提出一种基于视觉感知和菱形编码的图像隐写算法。根据人类视觉系统,针对人眼对图像的高中低灰度区、纹理区及平滑区的敏感度的不同,在不同区域选择嵌入不同数量的秘密信息;同时为了尽可能减少对图像像素值的改变,采用改进的菱形编码来嵌入秘密信息。实验结果表明,与HVS-OPAP算法相比,该算法图像的嵌入容量提高了4.09%,获取的隐写图像具有更好的不可感知性,同时峰值信噪比平均提高了1.5dB,而且该算法具有抗RS隐写分析能力,安全性更高。     

SOM和小波对比度在密写中的应用

为了提供较大的秘密信息嵌入量和保持较好的载密图像质量,提出了一种基于自组织特征映射神经网络和小波对比度的图像密写。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一级分解后计算小波对比度。然后,利用自组织特征映射神经网络将小块分为三类。最后,采用模算子技术嵌入秘密信息。实验结果表明,与WCL算法相比,该算法有更大的嵌入量并保持了良好的载密图像质量。     

基于相邻灰度值对互补嵌入的LSB匹配隐写改进算法

LSB匹配隐写具有嵌入量大.视觉隐蔽性高的优势,但采用LSB 匹配隐写算法对于载密图像的灰度直方图有明显的平滑作用,因此攻击者可以基于直方图分析图像是否载密.通过研究LSB匹配算法对直方图产生影响的机理,提出一种基于相邻灰度值互补嵌入的LSB 匹配改进算法.该算法利用匹配像素灰度值加减1对直方图的影响具有互补性的特点,以相邻灰度值匹配像素对为对象进行成对嵌入,有效地保持了直方图特性,极大地提高了算法的抗统计分析性能.     

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.     

Reversible steganography based on side match and hit pattern for VQ-compressed images

Data hiding is an important technique in multimedia security. Multimedia data hiding techniques enable message senders to disguise secret data by embedding them into cover media. Thus, delivering secret messages is as easy as sending the cover media. Recently, many researchers have studied reversible data hiding for images. Those methods can reconstruct the original cover image and extract the embedded secret data from a stego-image. This study proposes a novel reversible steganographic method of embedding secret data into a vector quantization (VQ) compressed image by applying the concept of side match. The proposed method uses extra information, namely the hit pattern, to achieve reversibility. Moreover, its small hit pattern enables the embedding of the entire hit pattern along with the secret data in most cases. To optimize visual quality of the output stego-image, the method applies the concept of partitioned codebooks (state codebooks). The partition operation on the codebook uses a look-up table to minimize embedding and extraction time. We also propose the use of diagonal seed blocks to embed the entire hit pattern into the cover image without producing any extra control messages. Compared to the Chang and Lin method, the experimental results show that the proposed method has higher capacity, better visual quality, and shorter execution time.     

A novel data hiding scheme based on modulus function

Four criteria are generally used to evaluate the performance of data hiding scheme: the embedding capacity, the visual quality of the stego-image, the security, and the complexity of the data-embedding algorithm. However, data hiding schemes seldom take all these factors into consideration. This paper proposes a novel data hiding scheme that uses a simple modulus function to address all the performance criteria listed above. According to the input secret keys, the encoder and decoder use the same set-generation functions H_r() and H_c() to first generate two sets Kr and Kc. A variant Cartesian product is then created using Kr and Kc. Each cover pixel then forms a pixel group with its neighboring pixels by exploiting an efficient modulus function; the secret data are then embedded or extracted via a mapping process between the variant of the Cartesian product and each pixel group. The proposed scheme offers several advantages, namely (1) the embedding capacity can be scaled, (2) a good visual quality of the stego-image can be achieved, (3) the computational cost of embedding or extracting the secret data is low and requires little memory space, (4) secret keys are used to protect the secret data and (5) the problem of overflow or underflow does not occur, regardless of the nature of the cover pixels.We tested the performance of the proposed scheme by comparing it with Mielikainen’s and Zhang and Wang’s schemes for gray-scale images. The experimental results showed that our proposed scheme outperforms Mielikainen’s in three respects, namely scalable embedding capacity, embedding rate, and level of security. Our data hiding scheme also achieved a higher embedding capacity than Zhang and Wang’s. The proposed scheme can easily be applied to both gray-scale and color images. Analyses of its performance showed that our proposed scheme outperforms Tsai and Wang’s in terms of its time complexity and memory space requirement.     

An adaptive steganographic method based on the measurement of just noticeable distortion profile

This paper presents an adaptive steganographic method based on just noticeable distortion (JND) profile measurement. According to the input requirements, our method can produce a higher quality or higher embedding capacity stego-image. In the embedding secret data bits into a target pixel process, four different impact factors are utilized to compute how much information can be embedded and what the stego-pixel value will be. These are difference values that represent the correlation between neighboring pixels, the JND value of the target pixel, a predefined embedding capacity control factor, and the contents of various lengths secret data bits. The proposed method embeds more secret data bits within complex areas and less data bits in smooth areas. The difference between the target pixel and the stego-pixel values is controlled, as far as possible, to less than or equal to the JND value of the target pixel. Thus, the stego-image maintains good imperceptible property. In the extraction phase, the embedded secret data can be extracted from the stego-image without referencing the original image and the JND profile. The experimental results show that our method improves stego-image quality and conspicuously increases the embedding capacity at the same time.     

Advanced image steganography based on exploiting modification direction and neutrosophic set

A new variant of image steganography based on exploiting modification directions (EMD) named advanced EMD (AEMD) is introduced. In this method the secret digits in mⁿ -ary notional systems are embedded into a group of n pixels of the cover image. To increase data hiding capacity, edge masking characteristics of human visual system is exploited to embed more bits at image edge pixels than non-edge pixels. To do this, a neutrosophic set edge detector, named as MNSED is also introduced to classify cover image into 2?×?2 non-overlapping edge and non-edge blocks without any overhead information. Hence the secret digits in two different bases are embedded into the edge and non-edge blocks. Experimental results show that the proposed method provides higher embedding capacity and better quality compared to the existing schemes, while its resistance to steganographic attack is still higher.

     

A reversible data hiding scheme based on the Sudoku technique

Data hiding, also known as information hiding, plays an important role in information security for various purposes. Reversible data hiding is a technique that allows distortion-free recovery of both the cover image and the secret information. In this paper, we propose a new, reversible data hiding scheme that is based on the Sudoku technique and can achieve higher embedding capacity. The proposed scheme allows embedding more secret bits into a pair of pixels while guaranteeing the good quality of the stego-image. The experimental results showed that the proposed scheme obtained higher embedding capacity than some other previous schemes. In addition, our proposed scheme maintained the good visual quality of the stego-image (i.e., PSNR > 46 dB), which outperforms some existing schemes.     

Data hiding based on extended turtle shell matrix construction method

Data hiding research has focused mainly on determining how to embed secret data into various public host media, and to also ensure the host medium is not changed to a degree such that it can be perceived by the human eye. In 2014, Chang et al. proposed a novel concept, named the turtle shell matrix, to embed secret data. This scheme has obvious advantages with respect to its hiding capacity and image quality. However, its disadvantage is lack of flexibility due to the fixed turtle shell matrix structure. In this paper, we extend this turtle shell matrix structure into a different matrix model to meet different hiding capacity and image quality needs. Meanwhile, a general extraction function is derived to generate a matrix having a different turtle shell model. The values of the pixel pairs in the cover image are modified according to guidance provided by the turtle shell to hide a secret digit in an N-ary notational system. The experimental results show that the proposed scheme not only has better flexibility in balancing the trade-off between hiding capacity and stego-image quality, but also provides higher hiding capacity and stego-images with better visual quality than previous schemes.