Stego-image Quality Research Articles

Modulus Calculations on Prime Number Algorithm for Information Hiding With High Comprehensive Performance

Information hiding is an important technique for information security, which is wildly studied by researchers. Recently embedding methods are proposed in spatial, frequency and other domains. After investigating previous literatures, we find that there is still room for embedding performance improvement. Inspired by some literatures, we propose a new method (Modulus Calculations on Prime Number Algorithm, MOPNA) for embedding secret data into cover-images. The main idea of MOPNA is hiding confidential data in paired cover-pixels with modulus calculation based on weight parameters consisting of prime numbers. MOPNA improves the embedding capacity while maintaining good stego-image quality. The correctness of MOPNA method is proved by a combination of mathematical and programming proof. The experimental results prove that the proposed method has high embedding capacity and achieves better comprehensive performance than existing methods.

An Effective Maximum Distortion Controlling Technology in the Dual-Image-Based Reversible Data Hiding Scheme

The dual-image information hiding method has received considerable research attention on account of its high hiding capacity and favorable stego-image quality. The dual-image hiding technology encodes secret data across two images, requiring both stego-images to recover the correct secret data. Many factors affect the embedding capacity and image quality of the dual-image hiding method, including the nature of the hidden data, the block size, and the method by which pixels are modified. This study analyzes and encodes secret data, while controlling the degree of pixel distortion using two parameters - NC and MXD to improve the image quality. The NC parameter controls how many codes are used to re-encode a secret symbol, which is used to control the number of code combinations. MXD specifies the maximum distortion of each code combination and is used to limit image distortion. To improve the effectiveness of the encoding, a pair of digital combinations was assigned according to the frequency of the secret numeric messages. A highly uniform secret message was encoded using a small distortion code. Subsequently, the code was concealed within the cover image, generating two stego-images. The experimental results indicate that the proposed method achieved not only a better embedding rate but also a greater image quality compared with previous methods. In particular, with regard to the smooth image, the image quality of the stego-image was higher than 64.27dB when the proposed scheme was applied. Furthermore, this study utilized many steganalytic technologies to validate the security of the proposed scheme.

Fidelity Preserved Data Hiding in Encrypted Images Based on Homomorphism and Matrix Embedding

This paper proposes a data hiding scheme for high quality stego-images in the encrypted images based on a homomorphic encryption algorithm and matrix embedding method. To achieve the message embedding in the encryption domain, we first present an image encryption algorithm satisfying additive homomorphism based on the stream cipher. Then, we offer a matrix embedding method using Golay code, which has good embedding efficiency. In the proposed scheme, we pre-code the least significant bit (LSB) vectors of the cover image into the codewords before image encryption, so that we can implement the matrix embedding in the encrypted image. The experimental results show that the proposed scheme has excellent security performance. We can get a high quality stego-image after the image decryption and recover the cover image into a fidelity image while providing considerable payload.

An Improved Bidirectional Shift-Based Reversible Data Hiding Scheme Using Double-Way Prediction Strategy

Reversible data hiding (RDH) is a method that allows a cover image to be completely recovered from its corresponding stego image without distortion after the embedded secret messages have been extracted. Prediction-error expansion (PEE), as a classic RDH scheme, has been studied extensively due to its high quality of stego images. Based on prediction errors, threshold values, and the relative distances between each bin and zero bin, we present a bidirectional shift and double-way prediction strategy to solve the multiple embedding problem. Compared with the original algorithm, this scheme only takes a little more time and reduces the PSNR slightly, but it improves the embedding capacity significantly and allows for reversible data hiding. When both threshold values of TH and TH∗ are equal to 2, the average ER value of 108 test images is 1.2 bpp which is ideal for medium data payload. At the same time, the PSNR is above 30 dB, making embedded information visually imperceptible. These data, together with other experimental results, show that the method proposed in this paper has obvious advantages in image quality and embedding capacity.

Efficient cover image selection based on spatial block analysis and DCT embedding

In steganography, the cover medium is widely treated as a mere container for the embedded information, even though it affects the stego-image quality, security, and robustness. In addition, there is no consensus on the characteristics of a suitable cover image. In this work, we introduce and practically prove the most suitable cover image (MSCI) framework to automatically select a cover image for a given secret image. This paper proposes choosing the most suitable cover from a set of images based on two steps. First, a set of cover images is filtered based on relative entropy and a histogram in order to identify the most suitable candidates. Second, the local block pixel intensity features of the candidates are analyzed to select the most suitable cover image. Furthermore, cover image local blocks were optimized, using rotation and flipping, during the embedding process to further improve stego-image representation. The proposed framework demonstrated high visual image quality when compared with existing solutions. Steganalysis tests indicated that the proposed solution for cover selection provided an increased resistance to modern steganalyzers with up to 30% lowered detection rate, which improved security.

Image Steganography using LSB and encrypted message with AES, RSA, DES, 3DES, and Blowfish

In today’s world, confidential information is growing due to various areas of works. Internet is the main area of transmission of digital data, so security must be more considered. Two common ways of providing security is cryptography and steganography. Employing a hybrid of cryptography and steganography enhances the security of data. This paper employs LSB (Least significant Bit) as the steganography algorithm and AES, RSA, DES, 3DES, and Blowfish algorithms as cryptographic algorithms to encrypt a message that should be hidden in a cover image. The results are represented in the form of execution time, PSNR (Peak Signal to Noise Ratio), MSE (Mean Square Error) and the histogram of main and covered image. The experimental results reveal that all the algorithms achieve appropriate quality of stego image. They can be used as cryptographic algorithms to encrypt a message before applying steganography algorithms.

A novel color image LSB steganography using improved 1D chaotic map

Conventional one-dimensional (1D) chaotic map have a simple structure, which is easy to implement and has a low computational cost, but has a drawback that the range of chaotic behaviors is narrow and the distribution of key sequence is uniform. In order to overcome the drawback, we proposed an improved 1D chaotic system model and evaluate the proposed model through experiments with the logistic map and a sine map. Simulation and performance evaluation shows that the 1D chaotic map improved by the proposed model can overcome the existing defects sufficiently. We also proposed a color image LSB steganography algorithm using the improved 1D chaotic map. Through experiments, we confirmed the accuracy of the proposed color image LSB steganography algorithm. Experimental results proved that the algorithm has a better performance than the previous methods, showing an excellent performance against statistical analysis attacks. We also analyzed the effect of secret data type on the quality of stego image.

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Improving the Quality of Stego Image Using Prediction Error and Histogram Modification

Image steganography based on color palette transformation in color space

In this paper, we present a novel image steganography method which is based on color palette transformation in color space. Most of the existing image steganography methods modify separate image pixels, and random noise appears in the image. By proposing a method, which changes the color palette of the image (all pixels of the same color will be changed to the same color), we achieve a higher user perception. Presented comparison of stegoimage quality metrics with other image steganography methods proved the new method is one of the best according to Structural Similarity Index (SSIM) and Peak Signal Noise Ratio (PSNR) values. The capability is average among other methods, but our method has a bigger capacity among methods with better SSIM and PSNR values. The color and pixel capability can be increased by using standard or adaptive color palette images with smoothing, but it will increase the embedding identification possibility.

PDA: A private domains approach for improved MSB steganography image

Steganography is one of the secure techniques of protecting data inside a cover object. Images are the most popular cover objects for Steganography. It provides secret message between users. The current paper presents an enhanced Most Significant Bit (MSB) technique. In this paper, a Private Domains Approach (PDA) is proposed; each domain consists of RGB of a pixel of cover image. Bit No.5 is applied to store the secret information in light of the bit that achieved highest steganography rate and the less probability of error rate.Consequently, this technique is allowing an improved version of MSB technique based on Mean-Squared Error (MSE), Peak Signal-to-Noise Ratio (PSNR). The experimental results show that our schemes perform well in terms of image quality. Generally; MSB technique produced the best stego-image quality in this paper.

Encrypted images-based reversible data hiding in Paillier cryptosystem

Homomorphic public key technology effectively protects privacy, allowing algebraic operations directly in the cipher-text. Therefore, it has been extensively studied in the field of cloud computing. In this study, an encrypted image-based data hiding (EIRDH) algorithm with homomorphic public key cryptosystem is presented. The key contributions are these two sides. (1) An improved fast Paillier homomorphic public key cryptosystem system is proposed for encrypting image. It improves the efficiency of encryption operations greatly. (2) A difference expansion (DE) scheme is developed by exploiting the cover pixel to construct a new pair of pixels for data hiding. Compared with other methods, the experimental results show that, the proposed method has larger payload and higher stego-image quality. It accomplishes the image quality’s increasing instead of general decreasing.

Histogram-based multilayer reversible data hiding method for securing secret data

In this modern age, data can be easily transferred within networks. This condition has brought the data vulnerable; so they need protection at all times. To minimize this threat, data hiding appears as one of the potential methods to secure data. This protection is done by embedding the secret into various types of data, such as an image. In this case, histogram shifting has been proposed; however, the amount of secret and the respective stego image are still challenging. In this research, we offer a method to improve its performance by performing some steps, for example removing the shifting process and employing multilayer embedding. Here, the embedding is done directly to the peak of the histogram which has been generated by the cover. The experimental results show that this proposed method has a better quality of stego image than existing ones. So, it can be one of possible solutions to protect sensitive data.

Improving Quality of Stego Images through Dithering Techniques for Pixel Pair Matching Steganographic Schemes

Steganography plays a vital role in sending any covert data via public media without hiding the covert channel. Due to visually imperceptible embedding process of secret, it is able to escape visual attacks. But when it is suspected, steganography can be detected by any efficient steganalysis techniques. It is an important aspect to improve the security of stego image if the information hidden is highly confidential, by improving the stego image quality. This paper presents a comprehensive analysis of deploying dithering (diffusion) techniques for enhancing the quality of stego images created by various Pixel Pair matching (PPM) steganographic algorithms. The dithering process attempts to keep the difference between original cover image and secret embedded stego image to a very minimum value. The quality of stego images is evaluated on parameters such as Peak Signal to Noise Ratio (PSNR), Structural SIMilarity index (SSIM), Net Pixel Change Rate (NPCR) and Unified Averaged Changed Intensity (UACI). Experimental results show that, depending on the type of steganographic algorithm used, the behaviour of dithering techniques differ and the choice of dithering must be made considering computational complexity of dithering process also.

Enhanced embedding capacity for the SMSD-based data-hiding method

The embedding capacity and stego-image quality are two important features in data-hiding schemes. In 2016, Kuo et al. introduced sparse modified signed-digit (SMSD)-based data hiding that could embed secret data into a group of n cover-pixels. Compared with previous exploiting modification direction (EMD) and generalized EMD (GEMD)-based data hiding, SMSD data hiding has higher embedding capacity and better stego-image quality. In this paper, we introduce a new definition of the enhanced MSD (EMSD) representation and propose an EMSD-based data-hiding scheme that improves the embedding capacity of SMSD data hiding and maintains equal quality of the stego-image. In addition, the embedding capacity in the proposed scheme is further improved using the section-wise approach in EMSD data hiding.

A high-capacity coverless image steganography method based on double-level index and block matching.

Recently, a new information hiding technology called coverless information steganography (CIS) is proposed, which uses the original natural image as stego image for the transmission of secret information which can resist the detection of image steganalysis algorithm, so it received extensive attention and support. However, it is still a low hidden capacity of the CIS methods up to now. This paper proposes a high-capacity coverless information steganography technology. In which we divide the cover image into several image blocks and every image block can represent one bit secret information which improves the capacity greatly. Then we retrieve the image blocks for replacement from the image block database based on secret information and then synthesize them into stego image. The quality of the stego image is still high because the required image blocks are similar to cover image blocks and they are all from natural images. Moreover, in order to improve the retrieval efficiency, we have established a double-level index structure. The experimental results show that compared with the existing CIS methods, the proposed method has larger capacity and better visual quality.

Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting

In recent years, reversible data hiding (RDH), a new research hotspot in the field of information security, has been paid more and more attention by researchers. Most of the existing RDH schemes do not fully take it into account that natural image’s texture has influence on embedding distortion. The image distortion caused by embedding data in the image’s smooth region is much smaller than that in the unsmooth region, essentially, it is because embedding additional data in the smooth region corresponds to fewer invalid shifting pixels (ISPs) in histogram shifting. Thus, we propose a RDH scheme based on the images texture to reduce invalid shifting of pixels in histogram shifting. Specifically, first, a cover image is divided into two sub-images by the checkerboard pattern, and then each sub-image’s fluctuation values are calculated. Finally, additional data can be embedded into the region of sub-images with smaller fluctuation value preferentially. The experimental results demonstrate that the proposed method has higher capacity and better stego-image quality than some existing RDH schemes.

An improved high capacity data hiding scheme using pixel value adjustment and modulus operation

High data hiding capacity, stego image quality and security are the measures of steganography. Of these three measures, number of bits that can be hidden in a single cover pixel, bits per pixel (bpp), is very important and many researchers are working to improve the bpp. Recently, to enhance the embedding capacity, some of the schemes were proposed which are based on the fixed equation that is used as an extraction function of secret data from the stego image. We propose an improved high capacity data hiding method that maintain the acceptable image quality that is more than 30 dB and improves the embedding capacity higher than that of the methods proposed in recent years. The method proposed in this paper uses n2 − ary notational system and achieves higher embedding rate of 4 bpp and also maintain the good visual quality.

An adaptive color image steganography method using adjacent pixel value differencing and LSB substitution technique

Steganography is a data-concealing technique that provides a covert communication. This paper proposes a spatial domain color steganography method that uses a neighboring pixel-pair differencing concept to enhance the embedding capacity. The proposed method considers the distortion tolerance capacity of each color plane and the difference value between two neighboring pixels while deciding the number of bits that can be concealed in that pixel-pair. Each plane is divided into some disjoint blocks of size 3 × 3 pixels. The method forms eight pairs of pixels in one block using the eight-neighboring pixel concept, which enables the method to utilize all the edge pixels in all probable directions. It also uses the XOR encoding technique before the embedding process. This step provides an additional layer of security to the secret information. The simulation results show that the proposed method is able to achieve a high embedding capacity with good visual quality as per the calculation of imperceptibility metrics. The robustness of the method is tested by RS steganalysis and pixel difference histogram analysis. Further, a comparison between the proposed method and the existing methods on the basis of embedding capacity and stego image quality is shown.

A new data encoding based on maximum to minimum histogram in reversible data hiding

ABSTRACTThe dual stego images based on data hiding has become popular in recent days. Since the embedding rate in dual stego images is very high. This paper proposes a new data encoding method based on maximum to the minimum histogram in reversible data hiding. This method estimates the encoded intensity from the message intensity and embeds the encoded intensity in the cover image. The stego image quality decreases the intensity of the hidden data which is high. The intensity of the data must be kept low to maintain a high-quality stego image. It is achieved using data encoding. Therefore, the proposed method uses new data encoding which converts the higher histogram data to lower intensity and the lower histogram data to higher intensity during the data embedding process. In the extraction process, the encoded intensities are decoded to message intensities to obtain the original data. The proposed data hiding approach has improved in terms of image quality (PSNR), structure similarity index measurements and embedding rate.

Reversible data hiding in binary images based on image magnification

Over the past few years, many methods have been proposed for reversible data hiding in digital images, but few have been applied to binary images. The existing methods mainly employ run-length to embed the secret message, but the capacity is low. In this paper, we propose a reversible data hiding method based on image magnification. Firstly, image cross-shape patterns are analyzed to select the reference block pattern. Then, to improve the capacity and ensure reversibility, an image magnification strategy based on the reference block pattern is designed to scale up the original image to get the reference image. Finally, to ensure the visual quality of stego image, an inner-block flippable pixel selection strategy is designed to embed data. Experimental results have demonstrated that the proposed reversible data hiding scheme can restore the original image after extracting the embedded message, and achieve high embedding capacity and good visual quality.