Data hiding scheme improving embedding capacity using mixed PVD and LSB on bit plane

In data hiding, pixel-value differencing and least significant bit are well-known techniques to embed secret data. In this paper, a novel data hiding scheme is proposed to provide high embedding capacity. In case of previous methods, pixel-value differencing and least significant bit techniques were used individually or in combination based on pixel, but the proposed method utilizes first by dividing the bit region and two schemes are used simultaneously in the same bit plane. The experimental results show that the proposed method has strength on embedding capacity maintaining visual image quality without distortion to the human eyes.     

一种基于LSB和PVD的图像信息隐藏方法研究

为了提高图像中秘密信息的嵌入量,提出并实现了一种基于最低有效位和像素值差异的图像信息隐藏方法。通过计算两个连续像素值的差异来判断图像的一致区域和边界区域,在一致区域使用最低有效位方法,而在边界区域使用像素值差异方法。实验结果表明,结合这两种方法后信息的嵌入量是单纯使用像素值差异方法的1.59～1.97倍,并且隐写图像具有大于38 dB的峰值信噪比,保证了隐写图像的视觉质量。     

High-capacity reversible data hiding method using block expansion in digital images

A reversible data hiding method allows recovery of the cover image after the secret data have been extracted. In this paper, a novel reversible data hiding method is proposed using neighboring interpolation and pixel-value differencing on block expansion. A consecutive embedding technique for a sub-block is proposed to maintain a higher embedding capacity, and a neighboring pixel-value referencing is also proposed to maintain a good visual quality in stego-images. The results of experiment demonstrate that the proposed method has higher capacity and maintains a better image quality than previous reversible data hiding methods.     

基于像素交换及时空混沌映射的信息隐藏方法

提出了一种在图像载体中进行信息隐藏的新方法。该方法通过硬c均值聚类分析,确定可嵌信息区域,在可嵌信息区域内的相邻像素间通过像素交换来编码信息。采用时空混沌置乱技术,控制秘密信息的嵌入过程,并对嵌入信息进行加密。该方案具有较好的视觉隐蔽性及统计隐蔽性,并且密钥空间大,实现了算法可公开的信息隐藏。     

A data hiding scheme using the varieties of pixel-value differencing in multimedia images

In this paper, a capacity promoting technique is proposed for embedding data in an image using pixel-value differencing (PVD). The PVD scheme embeds data by changing the difference value between two adjacent pixels so that more data is embedded into two pixels located in the edge area, than in the smooth area. In order to increase the embedding capacity, a new approach is proposed in this paper by searching edge area more flexibly. Instead of processing a pair of pixels at a time as proposed by Wu and Tsai, two pairs of pixels in a block are processed at the same time. In addition, we proposed a pixel-value shifting scheme to further increase the chances for embedding data. Our scheme exploits the edge areas more efficiently, thus leading to an increase in embedding capacity as shown by experimental results compared to Wu and Tsai's method. Also, the embedding result of our scheme passes the Fridrich et al.’s detection. Besides, according to the distribution of difference values, more practical range partitions are suggested for improving capacity.     

A more secure steganography based on adaptive pixel-value differencing scheme

Pixel-value differencing (PVD) based steganography is one of popular approaches for secret data hiding in the spatial domain. However, based on extensive experiments, we find that some statistical artifacts will be inevitably introduced even with a low embedding capacity in most existing PVD-based algorithms. In this paper, we first analyze the common limitations of the original PVD and its modified versions, and then propose a more secure steganography based on a content adaptive scheme. In our method, a cover image is first partitioned into small squares. Each square is then rotated by a random degree of 0, 90, 180 or 270. The resulting image is then divided into non-overlapping embedding units with three consecutive pixels, and the middle one is used for data embedding. The number of embedded bits is dependent on the differences among the three pixels. To preserve the local statistical features, the sort order of the three pixel values will remain the same after data hiding. Furthermore, the new method can first use sharper edge regions for data hiding adaptively, while preserving other smoother regions by adjusting a parameter. The experimental results evaluated on a large image database show that our method achieves much better security compared with the previous PVD-based methods.     

High-capacity image hiding scheme based on vector quantization

A novel grayscale image hiding scheme that is capable of hiding multiple secret images into a host image of the same size is proposed in this paper. The secret images to be hidden are first compressed by vector quantization with additional index compression process. Then, the compressed secret images are encrypted and embedded into the least-significant bits of the host pixels. To provide good image quality of the stego-image, the modulus function and the image property are employed to hide the secret bits into the host pixels and determine the number of hidden bits in each host pixel, respectively. According to the results, the proposed scheme provides a higher hiding capacity and a higher degree of security than that of the virtual image cryptosystem.     

An image interpolation based reversible data hiding scheme using pixel value adjusting feature

In this paper, we propose an image interpolation based reversible data hiding scheme using pixel value adjusting feature. This scheme consists of two phases, namely: image interpolation and data hiding. In order to interpolate the original image, we propose a new image interpolation method which is based on the existing neighbor mean interpolation method. Our interpolation method takes into account all the neighboring pixels like the NMI method. However, it uses different weight-age as per their proximity. Thus, it provides the better quality interpolated image. In case of data hiding phase, secret data is embedded in the interpolated pixels in two passes. In the first pass, it embeds the secret data into the odd valued pixels and then in the second pass, the even valued pixels are used to embed the secret data. To ensure the reversibility of the proposed scheme, the location map is constructed for every pass. Basically, the proposed scheme only increases/decreases the pixel values during data hiding phase, which improves the performance of the proposed scheme in terms of computation complexity. Experimentally, our scheme is superior to the existing scheme in terms of data hiding capacity, image quality and computation complexity.     

Reversible data hiding for high quality images exploiting interpolation and direction order mechanism

Reversible data hiding can restore the original image from the stego image without any distortion after the embedded secret message is exactly extracted. In this paper, a novel, reversible, data hiding scheme for high quality images is proposed in spatial domain. To increase embedding capacity and enhance image quality, the proposed scheme classifies all pixels as wall pixels and non-wall pixels. For wall pixel, the interpolation error is used to embed secret data over the interpolation prediction method. In contrast, the difference value between the non-wall pixel and its parent pixel, which is defined by the direction order, is computed to hide secret data based on the histogram shifting. The experimental results demonstrate that our scheme provides a larger payload and a better image quality than some existing schemes. Moreover, the performance of the proposed scheme is more stable for different images.     

Exploring pixel-value differencing and base decomposition for low distortion data embedding

This paper presents a low distortion data embedding method using pixel-value differencing and base decomposition schemes. The pixel-value differencing scheme offers the advantage of conveying a large amount of payload, while still maintaining the consistency of an image characteristic after data embedding. We introduce the base decomposition scheme, which defines a base pair for each degree in order to construct a two-base notational system. This scheme provides the advantage of significantly reducing pixel variation encountered due to secret data embedding. We analyze the pixel variation and the expected mean square error caused by concealing with secret messages. The mathematical analysis shows that our scheme produces much smaller maximal pixel variations and expected mean square error while producing a higher PSNR. We evaluate the performance of our method using 6 categories of metrics which allow us to compare with seven other state-of-the-art algorithms. Experimental statistics verify that our algorithm outperforms existing counterparts in terms of lower image distortion and higher image quality. Finally, our scheme can survive from the RS steganalysis attack and the steganalytic histogram attack of pixel-value difference. We conclude that our proposed method is capable of embedding large amounts of a message, yet still produces the embedded image with very low distortion. To the best of our knowledge, in comparison with the current seven state-of-the-art data embedding algorithms, our scheme produces the lowest image distortion while embedding the same or slightly larger quantities of messages.     

同态公钥加密系统的图像可逆信息隐藏算法

同态加密技术在加密信息、对信息进行隐私保护的同时,还允许密文数据进行相应的算术运算(如云端可直接对同态加密后的企业经营数据进行统计分析),已成为云计算领域的一个研究热点.然而,由于云存在多种安全威胁,加密后信息的安全保护和完整性认证问题仍然突出.另外,信息在加密后丢失了很多特性,密文检索成为了云计算需要攻克的关键技术.为了实现对加密图像的有效管理及其安全保护,本文提出了一种基于同态加密系统的图像可逆信息隐藏算法.该算法首先在加密前根据密钥选择目标像素,并利用差分扩展DE(Difference Expansion)的方法将目标像素的各比特数据嵌入到其它像素中.然后,利用Paillier同态加密系统对图像进行加密得到密文图像.在加密域中,利用待嵌入信息组成伪像素,加密后替换目标像素,完成额外信息的嵌入.当拥有相应的密钥时,接收方可以分别在密文图像或明文图像中提取出已嵌入的信息.当图像解密后,通过提取出自嵌入目标像素的各比特数据来恢复原始图像.实验仿真结果表明,该算法能够在数据量保持不变的前提下完成同态加密域中额外信息的嵌入,信息嵌入快速高效,并可分别从加密域和明文域中提取出嵌入的信息.     

一种新颖的图像自适应信息隐藏算法

在深入研究图像像素灰度差分的基础上,提出了一种新颖有效的自适应信息隐藏算法。该算法结合图像的局部特征,充分利用人类视觉的各种掩蔽特性以自适应地嵌入秘密信息,使得对原图像所作的改变具有很好的不可见性。实验结果表明,利用该算法进行信息隐藏易于实现,且具有较大的信息隐藏容量及一定的鲁棒性,从而缓解了信息隐藏系统各技术指标之间存在的矛盾。     

Adaptive Data Hiding in Edge Areas of Images With Spatial LSB Domain Systems

This paper proposes a new adaptive least-significant- bit (LSB) steganographic method using pixel-value differencing (PVD) that provides a larger embedding capacity and imperceptible stegoimages. The method exploits the difference value of two consecutive pixels to estimate how many secret bits will be embedded into the two pixels. Pixels located in the edge areas are embedded by a $k$-bit LSB substitution method with a larger value of $k$ than that of the pixels located in smooth areas. The range of difference values is adaptively divided into lower level, middle level, and higher level. For any pair of consecutive pixels, both pixels are embedded by the $k$-bit LSB substitution method. However, the value $k$ is adaptive and is decided by the level which the difference value belongs to. In order to remain at the same level where the difference value of two consecutive pixels belongs, before and after embedding, a delicate readjusting phase is used. When compared to the past study of Wu 's PVD and LSB replacement method, our experimental results show that our proposed approach provides both larger embedding capacity and higher image quality.      

A high capacity reversible data hiding scheme with edge prediction and difference expansion

To enhance the embedding capacity of a reversible data hiding system, in this paper, a novel multiple-base lossless scheme based on JPEG-LS pixel value prediction and reversible difference expansion will be presented. The proposed scheme employs a pixel value prediction mechanism to decrease the distortion caused by the hiding of the secret data. In general, the prediction error value tends to be much smaller in smooth areas than in edge areas, and more secret data embedded in smooth areas still meets better stego-image quality. The multiple-base notational system, on the other hand, is applied to increase the payload of the image. With the system, the payload of each pixel, determined by the complexity of its neighboring pixels, can be very different. In addition, the cover image processed by the proposed scheme can be fully recovered without any distortion. Experimental results, as shown in this paper, have demonstrated that the proposed method is capable of hiding more secret data while keeping the stego-image quality degradation imperceptible.     

一种改进的图像自适应信息隐藏算法

在深入分析图像像素灰度差分隐藏算法的基础上,提出了一种改进的自适应信息隐藏算法,它充分利用人类视觉的各种掩蔽特性,结合图像的局部特征以自适应地嵌入秘密信息,使得对原图像所做的改变具有更好的不可见性。实验结果表明,利用改进的算法进行信息隐藏易于实现,增加了图像的信息隐藏容量,提高了其鲁棒性,从而缓解了信息隐藏系统各技术指标之间存在的矛盾。     

A novel data hiding for color images based on pixel value difference and modulus function

This paper proposes a novel data hiding method using pixel-value difference and modulus function for color image with the large embedding capacity(hiding 810757 bits in a 512×512 host image at least) and a high-visual-quality of the cover image. The proposed method has fully taken into account the correlation of the R, G and B plane of a color image. The amount of information embedded the R plane and the B plane determined by the difference of the corresponding pixel value between the G plane and the median of G pixel value in each pixel block. Furthermore, two sophisticated pixel value adjustment processes are provided to maintain the division consistency and to solve underflow and overflow problems. The most importance is that the secret data are completely extracted through the mathematical theoretical proof.     

An encoding method for both image compression and data lossless information hiding

Reversible image data hiding technology means the cover image can be totally recovered after the embedded secret data is extracted. In this paper, we propose a reversible image data hiding scheme based on vector quantization (VQ) compressed images. The secret bits are embedded into the VQ index table by modifying the index value according to the difference of neighboring indices. The data hiding capacity and the size of the final codestream (embedded result) are a trade-off, and it can be decided by users. In other words, the proposed scheme has flexible hiding capacity ability. To estimate the performance, the proposed scheme was compared with the scheme proposed by Wang and Lu (2009). The results of the comparison showed that our proposed scheme is superior to the scheme proposed by Wang and Lu in both data hiding capacity and bit rate.     

基于纹理复杂度和差分的抗盲检测图像隐写算法

通过分析纹理复杂度对图像隐写分析的影响,提出一种基于纹理复杂度和像素差分的隐写算法。首先,将图像划分为大小相同的分块,通过分块中起点位置的不同计算分块中不同小块的纹理复杂度,选择复杂度最高的图像小块;然后,计算小块的相邻像素差分值,并根据秘密消息的长度和不同方向上的差分值分布确定嵌入阈值,在大于该阈值的差分值中嵌入秘密消息。对多种嵌入算法在不同图像库上做通用盲检测实验,实验结果表明,该算法在抵抗小波高阶统计量分析等盲检测算法能力方面,优于LSB匹配、图像边缘自适应嵌入等隐写算法。     

A TRIBUTE TO ALF MONGÉ

Abstract

A data hiding method using three-directional pixel-value differencing for gray images is presented in this article. The cover image is divided into non-overlapping 2 × 2 sub-blocks, and the basis pixel is selected to calculate three different values of a sub-block. Difference values are replaced by embedding the number of secret bits that are referenced by the range table. For three pixel pairs in the sub-block, the optimal pixel adjustment is preceded to reduce the distortion of visual quality. The experimental results demonstrate that the proposed method provides a high capacity and good visual quality.     

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.