A reversible data hiding scheme using complementary embedding strategy

Obtaining good visual quality and high hiding capacity with reversible data hiding systems is a technically challenging problem. In this paper, we propose a simple reversible data hiding scheme that uses a complementary hiding strategy. The proposed method embeds one secret bit horizontally and vertically into one cover pixel of a grayscale cover image by decreasing odd-valued pixels and increasing even-valued pixels by one. Experimental results show that the hiding capacity measured by bit per pixel (bpp) of the proposed scheme is at least 1.21 bpp with a PSNR (peak signal-to-noise ratio) value greater than 52 dB for all standard test images. Especially in the case of four-layer embedding, the PSNR value of the proposed method is still greater than 51 dB at a hiding capacity of about 5 bpp for all standard test images. In addition, the proposed method is quite simple because it primarily uses additions and subtractions. These results indicate that the proposed scheme is superior to many existing reversible data hiding schemes introduced in the literature.     

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 data hiding scheme with high embedding capacity and visual image quality based on SMVQ prediction through classification codebooks

This study exploits the characteristics of image blocks to develop an adaptive data hiding scheme that is based on SMVQ prediction. Since human beings’ eyes are highly sensitive to smooth images, changes in smooth cause great distortion and attract the attention of interceptors. Hence, this study proposes a data embedding scheme for embedding secret data into edge blocks and non-sufficiently smooth blocks. The experimental results show that the proposed scheme improves the quality of the stego-image and the embedding capacity.     

Development of a data hiding scheme based on combination theory for lowering the visual noise in binary images

In order to raise the embedding capacity and simultaneously reduce the artifact effect caused by embedding secret messages into binary images, a novel data hiding method based on the combination theory is proposed. In the proposed scheme, a secret position matrix is designed to improve the hiding capacity which is capable of preventing the least distortion based on the combination theory. Our new scheme enables users to conceal more than one bit of secret data by changing at most one pixel in one subimage. We have derived a formula for computing the payload and the possible modification pixels of a block. Compared with the existing schemes in terms of the hiding capacity and the visual artifacts, as our experimental results show, the proposed scheme is capable of providing a better image quality protector even with a more efficient secret data hider.     

Adaptive lossless steganographic scheme with centralized difference expansion

In this paper, a novel adaptive lossless data hiding scheme is presented that is capable of offering greater embedding capacity than the existing schemes. Unlike the fixed hiding capacity each block provides in most of the currently available lossless data hiding approaches, the proposed method utilizes a block-based lossless data embedding algorithm where the quantity of the hidden information each block bears is variable. To both reduce the image distortion and increase the hiding capacity, the payload of each block depends on its cover image complexity. Due to the fact that schemes with difference expansion tend to damage the image quality seriously in the edge areas, in the proposed scheme, smoother areas are chosen to conceal more secret bits. This way, a better balance can be reached between the embedding ratio and the stego-image quality. In addition, when recovered the cover image can came back to its old self to the last bit without any distortion at all. Experimental results, as this paper will show, have demonstrated that the proposed method is capable of hiding more secret data while maintaining imperceptible stego-image quality degradation.     

A path optional lossless data hiding scheme based on VQ joint neighboring coding

Data hiding is an important technique for covert communication that embeds secret data into a cover image with minimal perceptible degradation. Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but the cover media can be reconstructed without any distortion. In this paper, a novel path optional lossless data hiding scheme based on the joint neighboring coding (JNC) of the vector quantization (VQ) index table is proposed. The proposed scheme generates a VQ index table based on the cover image first. Next, according to an initial key and secret data content, different adjacent indices may be chosen to perform joint neighboring coding for each index and hide secret data. Finally, an appropriate output codestream is generated based on the minimal length principle. Our main contributions lie in three aspects: (1) the method combines the novel path_based shift method with the traditional JNC method to improve the capacity and stego image quality simultaneously. (2) The secret data extraction and cover image recovering processes are separated and both can be publicized to users. (3) The method is path optional to meet various users’ requirements. To testify the superiority of the proposed method, we compare it with the side match VQ (SMVQ)-based and modified fast correlation VQ (MFCVQ)-based algorithms. According to the experimental results, the proposed scheme outperforms the SMVQ-based and MFCVQ-based algorithms in four aspects, i.e., hiding capacity, stego image quality, transmission efficiency and security level.     

A novel high payload steganography scheme based on absolute moment block truncation coding

In this paper, we propose an efficient steganography method in the compressed codes of absolute moment block truncation coding (AMBTC). Many recent related schemes focus on implementing reversible data hiding in compressed AMBTC bit stream. However, the reconstructed image of AMBTC is already lossy and the strict reversibility severely limits embedding capacity. Due to the simplicity and regularity of AMBTC codes, implementing irreversible hiding scheme causes very slight loss visual distortion of reconstructed image in exchange of significant improve in embedding capacity. In proposed scheme, smoothness of AMBTC compressed trio is firstly detected, which is then indicated by substituting the LSB of high quantity level with flag bit. For smooth trios, the differences between both quantity levels are firstly encoded by Huffman coding and then concatenated with secret data to generate modified low quantity levels. Meanwhile, all bits in bit planes of smooth trios are substituted with secret data as well. For complex trio, secret bits are only embedded into quantity levels, which is similar to smooth trio except for the differences are encoded by Lloyd-Max quantization. Experimental results indicate that proposed scheme outperforms prior methods both in imperceptivity and embedding capacity, which confirms the effectiveness and superiority of our work.

     

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.     

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.     

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.     

Secure multi-group data hiding based on gemd map

Numerous data hiding schemes have been recently proposed based on section-wise strategy. The purpose of these approaches is to enhance security by using a unique key to generate a table. But these approaches are not matched between the embedding secret data length for binary bits and the length of the notation system in the section-wise strategy. In order to enhance the security of secret data and increase embedding capacity, we will propose a secure multi-group data hiding scheme based on General Exploiting Modification Direction (GEMD) map in this paper. Three major advantages exist in our scheme. First is flexibility for the number and combination of elements. Second is the removal of spatial redundancy in our method while maintaining embedding capacity above 1 bpp. Lastly, this method avoids the overflow/underflow problem. Experimental results show that our method enhances embedding capacity and maintains good visual stego image quality. In terms of security, the proposed scheme is more secure than LSB replacement method in terms of resisting visual attack and RS testing.     

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.     

Prediction-based reversible data hiding

For some applications such as satellite and medical images, reversible data hiding is the best solution to provide copyright protection or authentication. Being reversible, the decoder can extract the hidden data and recover the original image without distortion. In this paper, a reversible data hiding scheme based on prediction error expansion is proposed. The predictive value is computed by using various predictors. The secret data is embedded in the cover image by exploiting the expansion of the difference between a pixel and its predictive value. Experimental results show that our method is capable of providing a great embedding capacity without making noticeable distortion. In addition, the proposed scheme is also applicable to various predictors.     

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.     

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.     

An SMVQ-based reversible data hiding technique exploiting side match distortion

Secure online communication is a necessity in today’s digital world. This paper proposes a novel reversible data hiding technique based on side match vector quantization (SMVQ). The proposed scheme classifies SMVQ indices as Case 1 or 2 based on the value of the first state codeword’s side match distortion (SMD) and a predefined threshold t. The proposed scheme uses this classification to switch between compression codes designed for Cases 1 and 2 SMVQ indices. The length of these compression codes is controlled by the parameter ?. Thus, with the selection of appropriate ? and t values, the proposed scheme achieves good compression, creating spaces to embed secret information. The embedding algorithm can embed n secret bits into each SMVQ index, where n = 1, 2, 3, or 4. The experimental results show that the proposed scheme obtains the embedding rates of 1, 2, 3, or 4 bit per index (bpi) at the average bit rates of 0.340, 0.403, 0.465, or 0.528 bit per pixel (bpp) for the codebook size 256. This improves the performance of recent VQ and SMVQ-based data hiding schemes.     

A new steganographic method for color and grayscale image hiding

In this paper, we present a steganographic method for embedding a color or a grayscale image in a true color image. Three types of secret images can be carried by the proposed method: hiding a color secret image, hiding a palette-based 256-color secret image, and hiding a grayscale image in a true color image. Secret data are protected by the conventional crypto system DES. We compare the image quality and hiding capacity of the proposed method with those of the scheme in Lin et al.’s scheme. According to the experimental results, the image quality of the proposed method is better than that of the Lin et al.’s scheme. In addition, annotation data can be hidden with the secret image in the host image. The hiding capacity of the proposed method is greater than that of other compared schemes. The experimental results show that the proposed method is a secure steganographic method that provides high hiding capacity and good image quality.     

Extended squared magic matrix for embedding secret information with large payload

Data hiding is a technology designed for safely transmitting secret data through open communication channels, in which the secret data are embedded into a cover carrier imperceptibly. Among the existing data hiding schemes, the exploiting-modification-direction (EMD) based schemes draw considerable attentions due to large embedding capacity. The proposed scheme improves the EMD-2 scheme by constructing an extended squared magic matrix, resulting in a larger embedding capacity high up to 3.15 bits per pixel (bpp). Experimental results show that the proposed scheme outperforms state-of-the-art reference matrix based schemes in terms of embedding capacity, meanwhile, maintains good image quality.

     

Quadruple Difference Expansion-Based Reversible Data Hiding Method for Digital Images

ABSTRACT

Lossless data hiding is a special type of data hiding technique that guarantees not only the secret data but also the ability of cover media to be reconstructed without any distortion. A latest lossless data hiding technique is proposed by Hong Lin Jin's that is based on hiding only one data bit in the spatial domain in gray-level image. However, this method uses double difference expansion to embed bits which results in a small embedding capacity. For this purpose, we propose an improved algorithm with the potential of increasing the payload capacity and maintaining good image quality. The proposed improved algorithm is characterized by two aspects. First, the proposed improved reversible data hiding scheme is enhanced to exhibit data hiding in color palette images. Second, the embedding level is improved by using quadruple difference expansion to guarantee the embedding of 2-bit data into color images. Experiments of the proposed improved method have been conducted over several well-known test images. The results show that the proposed improved method significantly improves the embedding capacity over Hong Lin Jin's scheme by the range of 15–35% for grayscale images and 20–46% for color images while still maintaining the quality of the stego-images.     

基于图像秘密共享的密文域可逆信息隐藏算法

针对当前密文域可逆信息隐藏算法嵌入秘密信息后的携密密文图像的容错性与抗灾性不强,一旦遭受攻击或损坏就无法重构原始图像与提取秘密信息的问题,提出了一种基于图像秘密共享的密文域可逆信息隐藏算法,并分析了该算法在云环境下的应用场景。首先,将加密图像分割成大小相同的n份不同携密密文图像。然后,在分割的过程中将拉格朗日插值多项式中的随机量作为冗余信息,并建立秘密信息与多项式各项系数间的映射关系。最后,通过修改加密过程的内置参数,实现秘密信息的可逆嵌入。当收集k份携密密文图像时,可无损地恢复原始图像与提取秘密信息。实验结果表明,所提算法具有计算复杂度低、嵌入容量大和完全可逆等特点。在（3,4）门限方案中,所提算法的最大嵌入率可达4 bpp;在（4,4）门限方案中,其最大嵌入率可达6 bpp。所提算法充分发挥了秘密共享方案的容灾特性,在不降低秘密共享安全性的基础上,增强了携密密文图像的容错性与抗灾性,提高了算法的嵌入容量与云环境应用场景下的容灾能力,保证了载体图像与秘密信息的安全。