Pixel Value Differencing Method Research Articles

An interpolation based steganographic technique with least-significant-bit and pixel value differencing in a pixel block

Over the <span lang="EN-US">past few years, in order to improve the hiding capacity and the peak signal-to-noise ratio (PSNR) value, several steganographic techniques have been developed. Steganography has become a popular technique to transmit secret data through any medium. In image steganography, the human eye cannot easily identify the hidden data which is embedded into the image. Small changes are also not detected by the human eye. High hidden capacity along with high visual quality is provided by the pixel value differencing (PVD) method. This paper first proposes the method of interpolation between the pixel blocks and then applies the least-significant-bit (LSB) substitution technique with the PVD method. At the starting phase, the original image is fixedto a 2x2 block, then the nearest neighbor interpolation (NNI) technique is implemented. In the next phase, the upper left pixel isembedded by the k-bit LSB substitution method along with hidden data. The newly generated neighbouring pixel value is measured. Thus, data is hidden from three directions. Through this paper using two different range tables, the new algorithm is proposed. We observed that in both cases, PSNR and the hiding capacity are improved.</span>

A Comparative Analysis of LSB, MSB and PVD Based Image Steganography

Steganography is the art and science of hiding information by embedding data into cover media. Numerous techniques are designed to provide the security for the communication of data over the Internet. A good steganographic algorithm is recognized by the performance of the techniques measured with the support of the performance metrics among which are PSNR, MSE, SSIM, robustness and capacity to hide the information in the cover image. In this paper a comparative analysis of Least Significant Bit (LSB), Most Significant Bit (MSB) and Pixel Value Differencing (PVD) image steganography in grayscale and colored images was performed. Three different cover images was used to hide secret message. A comparative performance analysis of LSB, MSB and PVD methods used in image steganography was performed using peak signal to noise ratio (PSNR), Mean square error (MSE) and Structural Similarity index (SSIM) as performance metrics. LSB technique gives higher PSNR and SSIM values than MSB and PVD method with lower MSE than the other two techniques. Future research can be geared towards investigating the embedding capacity, security, and computational complexity of each technique. Keywords: Least Significant Bit (LSB), Most Significant Bit (MSB), Pixel value differencing (PVD), PSNR, SSIM and MSE,

Comparison of Least Significant Bit, Pixel Value Differencing, and Modulus Function on Steganography to Measure Image Quality, Storage Capacity, and Robustness

Information security is an important aspect of information. The importance of the value of information in every aspect can result in attempts to transfer access or theft of data and information by unauthorized parties. One technique for securing data and information is by applying the digital image steganography technique. Many methods can be used in steganography, some of which are Least Significant Bit (LSB), Pixel Value Differencing (PVD), and Modulus Function (MF). Good steganography must produce a stego-image with an image quality that is not different from the original image or what is called a cover image and has the storage capacity to store confidential data and is resistant to robustness. The purpose of this study was to compare the LSB, MF, and PVD methods to serve as alternatives to the use of steganography techniques. The results of this study indicate that the LSB method has the best image quality compared to the MF and PVD methods. For storage capacity, the PVD algorithm has a better capacity than the LSB and MF methods. Meanwhile, the robustness of the LSB, PVD, and MF methods has resistance to cropping with a percentage of 10% at the bottom of the stego-image.

Pixel Value Difference based Face Recognition for Mitigation of Secret Message Detection

Data security is an important aspect of the modern digital world. Authentication is necessary for the prevention of data from intruders and hackers. Most of the existing system uses textual password which can provide only single-layer security. The textual passwords are simple but they may prone to spyware as well as dictionary attacks. Hence there is a need for a highly secure and multilayer security method. Steganography, the art of hiding the existence of a message by embedding it into another medium, can be exploited in an authentication system. Steganography has emerged as a technology that introduced steganalysis to detect hidden information. In this approach, the multimedia file is the input that is to be transferred over the media. On the transmitter side, the audio and video files are extracted. The secret audio file is embedded with an audio file using the LSB method while the face of the authenticated person is embedded into the video frame using the Pixel Value Differencing (PVD) method. At the receiver side, the face is extracted using the reverse PVD method and authenticated using the Convolutional Neural Network-based face recognition method. After authentication, the secret audio is extracted using the reverse LSB method. The results show that the MSE, RMSE, PSNR, and SSIM of 0.0000045303, 0.0021, 53.5877, and 0.9957, respectively.

Efficient Pixel-Value Differencing Based Hybrid Steganographic Method Using Modulus Function

In the era of cloud computing and Big Data, steganographic methods are playing a pivotal role to provide security to sensitive contents. In the steganographic domain, pixel-value differencing (PVD) proposed by Wu and Tsai has been one of the most researched and popular methods as the PVD technique provides good quality stego-image along with high embedding capacity. This article extends the Wu and Tsai's work by proposing a new hybrid steganography scheme which works in two phases to increase the embedding capacity along with stego-image quality. In the first phase, the cover image is preprocessed using a segmentation table to make the image more robust for PVD method. In the second phase, the resultant image is partitioned into 2×1 pixels size blocks in a non-overlapping fashion and then modulus function based scheme is applied in reversible manner. Thus, a significant amount of secret data is embedded into the image. The experimental results prove that the proposed scheme has significantly improved in embedding capacity and quality as compared to the other related PVD-based methods.

Adaptive PVD and LSB based high capacity data hiding scheme

In this paper, a new data hiding scheme using a mixture of adaptive pixel value differencing (PVD) and least significant bit substitution (LSB) is proposed for increasing the data hiding capacity. The scheme is a generalization of Jung (J Real-Time Image Proc. 14:127–36, 2018) which is the first work to use PVD and LSB methods simultaneously on a single image. However, the PVD used by Jung (J Real-Time Image Proc. 14:127–36, 2018) is not an adaptive method means it does not consider the vertical and diagonal edges of the image for hiding the secret data. In the proposed scheme, the vertical and diagonal edges in addition to horizontal edges are used for hiding the secret data so that a large amount of secret data is hidden without any perceived change. Experimental results show that the performance of the proposed scheme is superior to the existing schemes in terms of both data hiding capacity and image quality. Moreover, it is very simple as it does not require much computation for embedding the secret data.

A New Reversible Data Hiding Technique Combined with Interpolation and Pixel Value Differencing Method

Steganography is the popular security method that provides complete security for communicating secret details. Image steganography is a very interesting field because of the imperceptible way of hiding data in images, since small distortion in the images cannot be identified by a human eye. This is the main idea to develop image steganography algorithms to improve visual quality. Pixel Value Differencing is able to provide a high quality stego image in spite of the high capacity of the concealed information. This paper proposes the first the interpolation techniques with the pixel block then applying then the Pixel Value Differencing method. Here in the first phase the original image is portioned into 2X2 block then applying the nearest neighbour interpolation technique after that in the second phase PVD is used to embed the secret data. Then the new pixel value of the neighbouring pixel also calculated. In this paper one variant are proposed by using single range table. We observed that for both the variant PSNR value and the hiding capacity are increased.

Dual Steganography Approach Using 3D Playfair Cipher and Pixel Value Differencing Method

In this paper we attempted to incorporate a text encoding technique 3D Playfair Cipher with Pixel Value Differencing (PVD) approach to achieve dual steganography. Dual steganography is very demanding in the present scenario, because steganography is only playing a role to stealth intruder, but sometimes existence of secret data got recognized, in such scenarios dual steganography can only protect our secret exchange. In steganography hiding capability is equally concerned as much as security, so compression of secret message is preferable before imparting it in cover medium. These requirements pushed us to implement a fast, secure, effective and handy steganographic approach to solve secure information exchange problems. In this research we took the advantage of 3D Playfair cipher not to only encode our secret message but also to reduce its size. Here dual steganography is formed using 3D Playfair cipher with PVD method. PVD method implements the concept that edge areas are more vulnerable that smooth areas in images to conceal secrets,which makes it a powerful approach in the field of image steganography due to its stegoimage quality and data hiding capabilities. PVD method hides data in cover image based on the difference of pixel value in the pixel pairs (nonoverlapping consecutive pixels). Proposed approach is much secure and better in data hiding capability along with ensuring better quality stego image quality, it also solves the problem of falling the boundary of the pixels presents in PVD method. Produced Stegoimage of proposed technique is secure enough against the RS detection attack and totally indistinguishable by human eyes.

Enhanced AMBTC based data hiding method using hamming distance and pixel value differencing

In this paper, we propose a new Absolute Moment Block Truncation Coding (AMBTC) based data hiding scheme using hamming distance and pixel value differencing methods. The proposed method firstly pre-processes the original image using a smoothing filter so that its quality can be maintained after AMBTC compression. It then applies AMBTC compression on the processed image and uses two thresholds to categorize the image blocks into three categories namely Smooth, Less_Complex, and Highly_Complex blocks so that the complex block can also be used to embed the secret data. The secret data is then embedded into the smooth blocks using simple replacement strategy. Further, the proposed method embeds 8 bits of secret data into the bit plane of Less_Complex blocks using hamming distance calculation and few bits into the quantization levels of Highly_Complex blocks using pixel value differencing (PVD) method to increase the data hiding capacity without having any major impact on image quality. Thus, the proposed method additionally embeds on average 6 more bits in complex blocks. Experimental results also prove that the proposed method is superior to the contemporary AMBTC based data hiding methods in term of data hiding capacity and has comparable image quality.

A High Payload Steganography Method based on Pixel Value Differencing

Steganography, a way for covert data communication, aims to send some secret messages via embedding them into digital image imperceptibly. This paper proposes a new adaptive steganography method based on the well-known pixel value differencing (PVD) technique. The method tries to enhance the payload of the hidden secret data and to improve the security of the stego-color image. To this end, the image is partitioned into 2-pixel blocks in a nonoverlapping fashion and scanned in a raster-scan order. The hiding payload of the original PVD method is investigated by considering two-directional edges: horizontal and diagonal directions with the color image. These directions are utilized in designing the proposed adaptive horizontal and vertical pixel value differencing (A-HDPVD) method. For improving the security, different numbers of secret bits are used for embedding adaptively in the two directions of each color pixel lie in the edges using the original PVD method. The experimental results show that the proposed method provides better visual quality and a high payload of the stego-image. Moreover, the proposed method is more robust against RS statistical steganalysis attacks.

Digital Image Steganography based on Seven Way Pixel Value Differencing

Background/Objectives: This paper presents a steganographic method by calculating the pixel value differences along seven directions using nine-pixel blocks. Methods/Statistical Analysis: The centrally located pixel in nine-pixel block is used to form seven pairs with its seven neighboring pixels. The eighth neighbor pixel is used as the indicator to identify whether a block suffers with Fall Off Boundary Problem (FOBP) or not. Findings: Seven pixel value differences are calculated and based on these differences embedding is done. After embedding, the central pixel value is normalized to have a single value for all the seven pairs by suitable adjustments. After adjustments if any pixel value in the block falls off boundary, then the entire block is exempted from embedding. This is noted at the eighth neighbor pixel, so that it can also be exempted during extraction. Furthermore, to increase the capacity and peak signal-to-noise ratio, the nine-pixel blocks which suffer with FOBP are embedded using Wu and Tsai’s PVD method. The extraction process is very simple and the secret message can be extracted from the stego-image without using the original cover image. Application/ Improvements: Without compromising the security and imperceptibility the hiding capacity is almost 50% increased as compared to Wu and Tsai’s Pixel Value Differencing (PVD) method.

Data embedding based on pixel value differencing and modulus function using indeterminate equation

An effective data hiding method based on pixel value differencing (PVD) and modulus function (MF) PVD (MF-PVD) was proposed. MF-PVD method was derived by Wang et al in which the MF was employed to adjust the remainder of two pixels for data embedding and extraction. In the proposed method, a new remainder function in a more general form is defined by selecting proper parameters, in which an indeterminate equation is constructed and an optimal solution is applied to revise the pixels. This strategy leads to a significant image distortion reduction compared with the original method. The experiment reveals that, by preserving the original embedding capacity, the method provides better embedding efficiency than both MF-PVD and PVD methods.

Adaptive image data hiding in edges using patched reference table and pair-wise embedding technique

Reference table (RT) based embedding method embeds secret digits into pixel pairs under the guidance of a reference table. Most of the existing RT-based methods either require elaborate conversions among different bases, or have limited embedding capacity. In this paper, we use a patched reference table (PRT) as a guide and propose a PRT method to provide a better image quality and extendable embedding capacity. We also exploit the concept of pixel value differencing (PVD) and propose another method PRT–PVD. In the traditional PVD-based methods, the shape of the difference histograms of the stego images is significantly altered and, thus, vulnerable to some steganalyzers. PRT–PVD adopts the PRT method and uses a specially designed embedding sequence to preserve the difference histogram shape. Experimental results reveal that the proposed PRT and PRT–PVD methods not only have better embedding efficiency over the existing methods, but also are robust to detection by modern steganalysis tools.

Colour Image Steganography based on Pixel Value Differencing in Spatial Domain

In a color image every pixel value composed of red, green and blue component and each of which ranges from 0 to 255 in case of 8-bit representation. In this paper, we have used pixel value differencing (PVD) method for secret data embedding in each of the component of a pixel in a color image. But when we use pixel-value differencing (PVD) method as image steganographic scheme, the pixel values in the stegoimage may exceed the range 0~255. We have eliminated this overflow problem of each component pixel. Furthermore for providing more security, we have used different number of bits in different pixel components. It would be very difficult to trace how many bits are embedded in a pixel of the stego image. From the experiments it is seen that the results obtained in proposed method provides better visual quality of stego-image compared to the PVD method.

High-capacity steganographic method based on pixel-value differencing and LSB replacement methods

In this paper, we propose a high capacity steganographic method using modulus function of pixel-value differencing (PVD) and least significant bit (LSB) replacement methods. Many steganographic methods based on LSB and PVD methods were presented to enlarge hiding capacity and provide an imperceptible image quality, but still have a room to improve the hiding capacity. The main idea of the proposed method is that secret data can be embedded on the smooth area by LSB substitution and on the edge area by PVD with less distortion to the human visual system and improvement of the embedding capacity. The experimental results show that the proposed method sustains a higher capacity and still a good quality compared with LSB and PVD methods.

Varied PVD + LSB evading detection programs to spatial domain in data embedding systems

Image steganographic schemes based on the least-significant-bit (LSB) replacement method own the character of high capacity and good quality, but they are detected easily by some programs. Pixel-value differencing (PVD) approaches are one kind of methods to pass some program detections, but PVD approaches usually provide lower capacities and larger distortion. Accordingly, the combined method of PVD and LSB replacement was proposed to raise the capacity and the quality of PVD approaches over the past literatures. In this paper, not only we contribute a new exploration in spatial domain to benefiting both the capacity and the fidelity on the basis of varied LSB + PVD approaches, but also the risk of the RS-steganalysis detection program is evaded. Furthermore, proof works are conducted to proclaim the correctness of the general LSB + PVD method. Following up, the varied LSB + PVD approach is therefore applied to our scheme.

Secure Bit-Plane Based Steganography for Secret Communication

A secure method for steganography is proposed. Pixel-value differencing (PVD) steganography and bit-plane complexity segmentation (BPCS) steganography have the weakness of generating blocky effects and noise in smooth areas and being detectable with steganalysis. To overcome these weaknesses, a secure bit-plane based steganography method on the spatial domain is presented, which uses a robust measure to select noisy blocks for embedding messages. A matrix embedding technique is also applied to reduce the change of cover images. Given that the statistical property of cover images is well preserved in stego-images, the proposed method is undetectable by steganalysis that uses RS analysis or histogram-based analysis. The proposed method is compared with the PVD and BPCS steganography methods. Experimental results confirm that the proposed method is secure against potential attacks.

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 et al.'s PVD and LSB replacement method, our experimental results show that our proposed approach provides both larger embedding capacity and higher image quality.

Image steganographic scheme based on pixel-value differencing and LSB replacement methods

In order to improve the capacity of the hidden secret data and to provide an imperceptible stego-image quality, a novel steganographic method based on least-significant-bit (LSB) replacement and pixel-value differencing (PVD) method is presented. First, a different value from two consecutive pixels by utilising the PVD method is obtained. A small difference value can be located on a smooth area and the large one is located on an edged area. In the smooth areas, the secret data is hidden into the cover image by LSB method while using the PVD method in the edged areas. Because the range width is variable, and the area in which the secret data is concealed by LSB or PVD method are hard to guess, the security level is the same as that of a single using the PVD method of the proposed method. From the experimental results, compared with the PVD method being used alone, the proposed method can hide a much larger information and maintains a good visual quality of stego-image.

Vulnerability of pixel-value differencing steganography to histogram analysis and modification for enhanced security

The pixel-value differencing (PVD) steganography can embed a large amount of secret bits into a still image with high imperceptibility as it makes use of the characteristics of human vision sensitivity. However, a loophole exists in the PVD method. Unusual steps in the histogram of pixel differences reveal the presence of a secret message. An analyst can even estimate the length of hidden bits from the histogram. To enhance security, a modified scheme is proposed which avoids occurrence of the above-mentioned steps in the pixel difference histogram while preserving the advantage of low visual distortion of the PVD. The histogram-based steganalysis is therefore defeated.