High Stego-image Quality Research Articles

Enhanced stego block chaining (ESBC) for low bandwidth channels

AbstractThis paper presents a new enhanced stego block chaining (ESBC) technique for data hiding to address the bandwidth and transmission time issues of simple stego block chaining (SBC). In simple SBC data hiding method, the security of the hidden information is increased by increasing the number of stages, but the addition of each stage decreases the hiding capacity. This increases the size of the data needed to transmit the secret message and thus results in an increase in the required bandwidth and transmission time. The proposed ESBC technique addresses the bandwidth and transmission time issues of the simple SBC method. The output of the ESBC is a high quality stego image with peak signal‐to‐noise ratio above 40 dB and provides the same additional security as simple SBC but reduces the requirements of the bandwidth and transmission time by one half of that of the simple SBC and, thus, solves the hiding capacity issues of SBC for low bandwidth channels. Copyright © 2017 John Wiley & Sons, Ltd.

Reversible data hiding algorithm using spatial locality and the surface characteristics of image

In this paper, we propose a very efficient reversible data hiding algorithm using spatial locality and the surface characteristics of image. Spacial locality and a variety of surface characteristics are present in natural images. So, it is possible to precisely predict the pixel value using the locality and surface characteristics of image. Therefore, the frequency is increased significantly at the peak point of the difference histogram using the precisely predicted pixel values. Thus, it is possible to increase the amount of data to be embedded in image using the spatial locality and surface characteristics of image. By using the proposed reversible data hiding algorithm, visually high quality stego-image can be generated, the embedded data and the original cover image can be extracted without distortion from the stego-image, and the embedding data are much greater than that of the previous algorithm. The experimental results show the superiority of the proposed algorithm.

A secure image sharing scheme with high quality stego-images based on steganography

Image sharing can be utilized to protect important commercial, military or private images against a single point of failure. Many existing image sharing schemes may have one or more of the security weaknesses as follows: First, noise-like image shares may easily arouse the attackers' attention; Second, cheating in the recovery of the secret image cannot be prevented effectively; Third, the requisite size of cover images may be very large; Finally, poor quality of the stego-images may lessen camouflage effects. In this paper, a novel secure image sharing scheme with high quality stego-images is proposed. With the use of LOCO-I compression as a preprocessing approach, the statistical correlations between neighboring pixels of a secret image drop significantly, which may greatly enhance the visual security of the proposed scheme. And the necessary size of cover images is reduced. Moreover, the PSNR values of stego-images are much higher than the related works. In order to detect three kinds of deception during secret image reconstruction, the hash-based message authentication codes of an image share, the value of argument x and the identity ID of a participant are embedded into a cover image together with the image share. In addition, the application of dynamic embedding with a random strategy further enhance the security of our scheme.

An advanced reversible data hiding algorithm based on the similarity between neighboring pixels

In this paper, an advanced reversible data hiding algorithm which takes the advantage of the spatial locality in image was proposed. Natural image has a spatial locality. The pixel value of a natural image is similar to the values of neighboring pixels. So, using the neighboring pixel values, it is possible to precisely predict the pixel value. Frequency increases significantly at the peak point of the difference histogram using the predicted values. Therefore, it is possible to increase the amount of data to be embedded. By using the proposed algorithm, visually high quality stego-image can be generated, the original cover image and the embedded data can be extracted from the stego-image without distortion. The embedding data into the cover image of the proposed algorithm is much lager than that of the previous algorithm. The performance of the proposed algorithm was verified by experiment. The proposed algorithm is very useful for the reversible data hiding.

An efficient multi-predictor reversible data hiding algorithm based on performance evaluation of different prediction schemes

With the broad development and evolution of digital data exchange, security has become an important issue in data storage and transmission since digital data can be easily manipulated and modified. Reversible data hiding algorithms are special class of steganography that are capable of recovering the original cover image upon the extraction of the secret data. This issue is of interest in medical and military imaging applications. Many algorithms in this class exploit the idea of prediction in order to increase the embedding capacity as well as the quality of the stego image. However, the performance of these algorithms depends on the type of predictor that is being used. The main goal in this paper is to survey different predictors and evaluate their performance when employed in two classical reversible data hiding algorithms. The evaluation considered plugging 22 predictors in the two algorithms to process 1438 test images. Experimental results validated the varying capabilities of different predictors and showed that the non-causal median predictor had the best performance in the two algorithms. Further more, the paper proposes a new multi-predictor reversible data hiding algorithm. Basically, the algorithm employs multiple predictors in an extended version of the modification of prediction errors (MPE) algorithm. The algorithm takes advantage of the results obtained from the performance evaluation of different predictors to select the best set of predictors. Performance evaluation proved the ability of the proposed algorithm in increasing the embedding capacity while maintaining high stego image quality.

Data Security Using Cryptography and Steganography Techniques

Although cryptography and steganography could be used to provide data security, each of them has a problem. Cryptography problem is that, the cipher text looks meaningless, so the attacker will interrupt the transmission or make more careful checks on the data from the sender to the receiver. Steganography problem is that once the presence of hidden information is revealed or even suspected, the message is become known. According to the work in this paper, a merged technique for data security has been proposed using Cryptography and Steganography techniques to improve the security of the information. Firstly, the Advanced Encryption Standard (AES) algorithm has been modified and used to encrypt the secret message. Secondly, the encrypted message has been hidden using method in [1]. Therefore, two levels of security have been provided using the proposed hybrid technique. In addition, the proposed technique provides high embedding capacity and high quality stego images

Rate and Distortion Optimization for Reversible Data Hiding Using Multiple Histogram Shifting.

Histogram shifting (HS) embedding as a typical reversible data hiding scheme is widely investigated due to its high quality of stego-image. For HS-based embedding, the selected side information, i.e., peak and zero bins, usually greatly affects the rate and distortion performance of the stego-image. Due to the massive solution space and burden in distortion computation, conventional HS-based schemes utilize some empirical criterion to determine those side information, which generally could not lead to a globally optimal solution for reversible embedding. In this paper, based on the developed rate and distortion model, the problem of HS-based multiple embedding is formulated as the one of rate and distortion optimization. Two key propositions are then derived to facilitate the fast computation of distortion due to multiple shifting and narrow down the solution space, respectively. Finally, an evolutionary optimization algorithm, i.e., genetic algorithm is employed to search the nearly optimal zero and peak bins. For a given data payload, the proposed scheme could not only adaptively determine the proper number of peak and zero bin pairs but also their corresponding values for HS-based multiple reversible embedding. Compared with previous approaches, experimental results demonstrate the superiority of the proposed scheme in the terms of embedding capacity and stego-image quality.

Reversible Data Hiding Based on Geometric Structure of Pixel Groups

Many reversible data hiding schemes have been developed in recent decades. Traditional schemes typically must deal with the problem of overow and underow, or transmission of hiding parameters. The new reversible data hiding scheme proposed in this paper is based on a combination of pixel groups' geometric structure and secret sharing mechanism. Experimental results confirm that the proposed scheme not only achieves the goal of hiding information without memorization of location map or any other parameter, but also generates very high quality stego-images with very large capacity of secret information embedded.

Performance enhanced image steganography systems using transforms and optimization techniques

Image steganography is the art of hiding highly sensitive information onto the cover image. An ideal approach to image steganography must satisfy two factors: high quality of stego image and high embedding capacity. Conventionally, transform based techniques are widely preferred for these applications. The commonly used transforms for steganography applications are Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT) etc. In this work, frequency domain transforms such as Fresnelet Transform (FT) and Contourlet Transform (CT) are used for the data hiding process. The secret data is normally hidden in the coefficients of these transforms. However, data hiding in transform coefficients yield less accurate results since the coefficients used for data hiding are selected randomly. Hence, in this work, optimization techniques such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used for improving the performance of the steganography system. GA and PSO are used to find the best coefficients in order to hide the Quick Response (QR) coded secret data. This approach yields an average PSNR of 52.56 dB and an embedding capacity of 902,136 bits. These experimental results validate the practical feasibility of the proposed methodology for security applications.

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent techniques

An Image Steganography Algorithm for Hiding Data Based on HDWT, LZW and OPAP

Image steganography is the art of information hiding, which embeds a secret data into a cover image. However, high capacity of secret data and high quality of stego image are key issues in image steganography. In this paper, an image steganography technique based on Haar Discrete Wavelet Transform (HDWT), Lempel Ziv Welch (LZW) algorithm and Optimal Pixel Adjustment Process (OPAP) is proposed. The HDWT is used to increase the robustness of stego image against attacks. To increase the hidden capacity, LZW algorithm is performed on the secret message. The OPAP is then applied to reduce the embedding error between the cover image and stego image. The experimental results are evaluated by four standard images as covers, and with two types of secret messages. The results demonstrate high visual quality of stego image with large Hidden Capacity (HC) of secret data compared with recent techniques

Frequency domain QR code based image steganography using Fresnelet transform

Image steganography is the art of hiding secret message onto the source image. A good approach to steganography must provide two attributes: high stego image quality and high embedding capacity. In this paper, a frequency domain steganography based information hiding technique using Fresnelet transform (FT), has been proposed. In this method, the Fresnelet coefficients of the Least Significant Bit (LSB) at high frequency subbands are used to embed the QR coded secret message. This approach yields an average PSNR of 45.40dB and an embedding capacity of 352,332 bits. These results validate the practical feasibility of the proposed method for security applications.

Comparison of LSB and Predictive Coding using PSNR and MSE

In the era of internet, in every communication images play a very important role. Images are used for secret communication also like for military purposes, hiding the serial number or copyright also to embed the virus and other bad things etc. To hide data in image in such a way that the existence of the message is unknown is steganography. Different techniques are used to hide data in the image to achieve high quality of stego image and high embedding capacity. In this paper, two steganographic techniques re used i.e. LSB and predictive coding. The stego image which is formed by both the techniques are then compared using two parameters i.e. PSNR and MSE

A Data Hiding Scheme for Grayscale Images Using a Square Function

Many image hiding schemes based on least significant bit (LSB) transformation have been proposed. One of the LSB-based image hiding schemes that employs diamond encoding was proposed in 2008. In this scheme, the binary secret data is converted into base n representation, and the converted secret data is concealed in the cover image. Here, we show that this scheme has two vulnerabilities: noticeable spots in the stego-image, i.e., a non-smooth embedding result, and inefficiency caused by rough re-adjustment of falling-off-boundary value and impractical base translation. Moreover, we propose a new scheme that is efficient and produces a smooth and high quality embedding result by restricting n to power of 2 and using a sophisticated re-adjustment procedure. Our experimental results show that our scheme yields high quality stego-images and is secure against RS detection attack.

Secured and Robust Information Hiding Scheme

The sensitivity of the digital work made it susceptible to many accidental dangers. Accordingly, it has become necessary for the secret data to be protected, identified and extracted. As a result, many researchers have exerted much of their time and efforts in an attempt to find suitable ways for data hiding. As a case in point is the development of steganography, a technique used for hiding the important information imperceptibly. As far as the present work is concerned, the researcher adopts the steganography system for the purpose of embedding secret data within the frequency domain. Such a step can be done by modifying the DCT coefficients in a content-based manner, so that the embedding map will be able to easily identify the embedding blocks; a matter which in turn helps recover the data hidden in the frequency domain. The arrived at results reflected the manageability of the system to fight against AWGN and JPEG compression attacks and a high quality stego-images. However, being only part of an image is used for the purpose of hiding data has limited the capacity of the system in this regards.

A Novel Security Scheme for Secret Data using Cryptography and Steganography

With the development of network techniques the problem of network security becomes more and more important. The use of Word Wide Web has grown extremely in the past few years. Furthermore, many end users can easily use tools to synthesize and edit multimedia information. Thus, security has become one of the most significant problems for distributing new information technology. It is necessary to protect this information while communicated over insecure channels. Thus, a need exists for developing technology that will help protect the integrity of digital content and secure the intellectual property rights of owners. Cryptography and Steganography are the two major techniques for secret communication. The contents of secret message are scrambled in cryptography, where as in steganography the secret message is embedded into the cover medium. In this proposed system we developed high security model by combining cryptographic and Steganographic security. In cryptography we are using advanced encryption standard (AES) algorithm to encrypt secret message and then pixel value differencing (PVD) with K-bit least-significant-bit (LSB) substitution is used to hide encrypted message into truecolor RGB image. Our proposed model gives two tier security to secret data. Further our proposed method gives high embedding capacity and high quality stego images.

A Lossless Large-Volume Data Hiding Method Based on Histogram Shifting Using an Optimal Hierarchical Block Division Scheme

A lossless large-volume data hiding method based on histogram shifting is proposed. The method is based on a scheme of hierarchically dividing a cover image into smaller blocks for data embedding using the histogram shifting technique, which yields a large data hiding capacity and results in a high stego-image quality. A technique for recursive looking-ahead estimation of the maximum data hiding volume at the lowest level of the block-division tree structure is proposed to yield an optimal data hiding result. The technique is shown to break a bottleneck of data-hiding-rate increasing at the image block size of 8 × 8, which is found to exist in other histogram-shifting methods. Four ways of block divisions are used, and one of them is selected optimally in each tree level of block divisions. A series of experiments have been conducted, and superiority of the proposed method to other related methods is shown by comparing the respective experimental results. A good property of the proposed method observed in the experiments is also pointed out, that is, the data hiding rate yielded by the proposed method increases without degrading the stego-image quality, which is an unusual phenomenon in data hiding researches.

A High Capacity Steganographic Technique based on LSB and PVD Modulus Methods

many novel image steganographic techniques have been proposed in the recent years, PVD modulus method produces high quality stego images, when compared with other methods. But a significant drawback of PVD modulus method is low capacity. The hiding capacity is extremely low in PVD modulus method, when compared with other methods like LSB, etc. The reason for the low hiding capacity is that, with PVD modulus method we divide the pixel blocks in to smooth blocks where, the pixel value difference is low and edge blocks where the pixel value difference is high. In this paper, we propose a technique, which is a combination of PVD modulus and LSB method. As per the experimental results hiding capacity increases enormously. KeywordsLSB Method, PVD Modulus Method.

Secret image sharing with authentication-chaining and dynamic embedding

Abstract A popular technique to share a secret image among n participants is to divide it first into some shadow images and then embed the shadows in n”cover” images. The resulting “stego” images, which contain the embedded data, are distributed among intended recipients. In order not to attract any attacker’s attention, it is important to apply a suitable embedding such that high quality stego images are produced. Moreover, to ensure the integrity of stego data, a robust authentication mechanism which can detect tampering with high probability should be implemented. Recently, a series of papers ( Lin and Tsai, 2004; Yang et al., 2007; Chang et al., 2008; Yang and Ciou, 2009) have considered polynomial-based secret image sharing with steganography and authentication. The embedding technique employed in all these papers is static, i.e. hidden bits are embedded in predetermined fixed-size blocks of each cover image. It is therefore possible that all the hidden data is replaced in only a subset of blocks of cover images while other blocks remain intact. As for authentication, the best of these schemes detects a tampered stego block with probability 15/16, however, since this is obtained at the cost of using 4 authentication bits per block, the visual quality of stego images is seriously degraded. In this paper, we propose a novel polynomial-based secret image sharing scheme with two achievements. First, a new embedding is proposed so that the block size is determined dynamically according to the size of hidden data and therefore, all the capacity of cover images is used for data hiding. Second, we introduce a new authentication-chaining method which achieves 15/16 as its tamper-detection ability while using only 2 authentication bits. Experimental results are provided to confirm the theory.

Reversible data embedding for high quality images using interpolation and reference pixel distribution mechanism

This paper proposes a reversible data hiding method based on image interpolation and the detection of smooth and complex regions in the cover images. A binary image that represents the locations of reference pixels is constructed according the local image activity. In complex regions, more reference pixels are chosen and, thus, fewer pixels are used for embedding, which reduces the image degradation. On the other hand, in smooth regions, less reference pixels are chosen, which increases the embedding capacity without introducing significant distortion. Pixels are interpolated according to the constructed binary image, and the interpolation errors are then used to embed data through histogram shifting. The pixel values in the cover image are modified one grayscale unit at most to ensure that a high quality stego image can be produced. The experimental results show that the proposed method provides better image quality and embedding capacity compared with prior works.