Embedding Secret Data Research Articles

Data-Hiding Scheme Using Multidirectional Pixel-Value Differencing on Colour Images

Data hiding is a technique that hides the existence of secret data from malicious attackers. In this paper, we propose a new data-hiding scheme using multidirectional pixel-value differencing, which can embed secret data in two directions or three directions on colour images. The cover colour image is divided into nonoverlapping blocks, and the pixels of each block are decomposed into R, G, and B channels. The pixels of each block perform regrouping, and then the minimum pixel value within each block is selected. The secret data can be embedded into two directions or three directions based on the minimum pixel value by using the difference value for the block. The pixel pairs with the embedded secret data are put separately into two stego images for secret data extraction on receiver sides. In the extraction process, the secret data can be extracted using the difference value of the two stego images. Experimental results show that the proposed scheme has the highest embedding capacity when the secret data are embedded into three directions. Experimental results also show that the proposed scheme has a high embedding capacity while maintaining the degree of distortion that cannot be perceived by human vision system for two directions.

Imperceptible Steganography Scheme with High Payload Capacity using Genetic Algorithm and Particle Swarm Optimization

Security is the most significant parameter in all type of confidential data transfers. Steganography is used to enhance the security of such confidential communications. Steganography is a method of covert communication in which the existence of secrecy is concealed. In image steganography, achieving high data embedding capacity and simultaneously retaining good visual quality is a very tricky and difficult objective. In this paper, a reversible, secure, extremely imperceptible and high payload capacity steganography technique in the spatial domain is proposed. The proposed method employs evolutionary computation techniques to identify the most optimum locations and arrangements for secret data embedding. The proposed technique uses Particle Swarm Optimization to find the best possible order of data hiding whereas Genetic algorithm is used to identify the best possible arrangements to modify secret data to produce least amount of change in cover-image. The result of the proposed scheme is compared with many steganography techniques and the proposed scheme outperforms the existing schemes in terms of imperceptibility. The proposed technique produces an average PSNR value of 46.40 dB at 2 bit per pixel data embedding rate.

Digital watermarking techniques for image security: a review

Multimedia technology usages is increasing day by day and to provide authorized data and protecting the secret information from unauthorized use is highly difficult and involves a complex process. By using the watermarking technique, only authorized user can use the data. Digital watermarking is a widely used technology for the protection of digital data. Digital watermarking deals with the embedding of secret data into actual information. Digital watermarking techniques are classified into three major categories, and they were based on domain, type of document (text, image, music or video) and human perception. Performance of the watermarked images is analysed using Peak signal to noise ratio, mean square error and bit error rate. Watermarking of images has been researched profoundly for its specialized and modern achievability in all media applications such as copyrights protection, medical reports (MRI scan and X-ray), annotation and privacy control. This paper reviews the watermarking technique and its merits and demerits.

High fidelity based reversible data hiding using modified LSB matching and pixel difference

Owing to the inefficiency to hide large volume of secret data for the reversible data hiding (RDH) image steganography approaches, we propose two improved RDH based approaches, such as (1) improved dual image based least significant bit (LSB) matching with reversibility, and (2) n-rightmost bit replacement (n-RBR) and modified pixel value differencing (MPVD). The first approach extends the ability of LSB matching with reversibility using dual images. Whereas the second approach utilizes four identical cover images for secret data embedding using two phases, such as (1) n-rightmost bit replacement (n-RBR) and (2) modified pixel value differencing (MPVD). In the n-RBR phase, n bits of secret data are embedded in the pair of two neighboring pixels of the first two identical images, where 1 ≤ n ≤ 4. Correspondingly, the MPVD phase uses the third and fourth identical images for hiding the secret data. Experimental results with respect to peak signal-to-noise ratio (PSNR), embedding capacity (EC), structural similarity index (SSIM), and the comparative analysis with recently proposed state-of-art approaches exhibit the superiority of the proposed approach. Besides reversibility, the proposed approach ensures high fidelity to salt and pepper (S&P) noise, RS analysis, and pixel difference histogram (PDH) analysis.

STEGANALYSIS OF DIGITAL IMAGES UNDER DIFFERENT CONTENT FULLNESS

An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stegano formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stegano was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.

A Mini-Sudoku Matrix-Based Data Embedding Scheme With High Payload

Data hiding is a technology that generates meaningful stego media by embedding secret data in the cover media. In this paper, we propose a novel data hiding scheme using a mini-Sudoku matrix (MSM). A candidate block associated with the mapping value of a cover pixel pair on the MSM is used to indicate where the original pair would be modified to. According to the candidate block, each non-overlapping pixel pair can embed four bits of secret data. Among them, the first two bits are mapped from a specific element in the MSM while the other two are represented by the horizontal and vertical coordinates of this element with the modulus function. In addition, our MSM can be easily extended, and the proposed method can be used in other magic matrices to increase their embedding capacities. The experimental results indicate that our proposed scheme provides images with better visual quality than the previous methods. Furthermore, the security of the proposed scheme is verified by using pixel difference histogram (PDH) and RS steganalysis.

Reversible Data Hiding Scheme Based on Quad-Tree and Pixel Value Ordering

This study proposes a reversible data hiding (RDH) scheme based on pixel value ordering (PVO). RDH schemes based on PVO technique generally realize the prediction procedure by employing the sorted pixels in a block-wise manner, and then embedding secret data by expanding the prediction errors. Since these operations are carried out based on the block, and pixel intensity has spatial correlation such that the neighboring pixels have similar values, the block patterns and sizes certainly affect the embedding performance of the PVO-based RDH method. The original PVO-based RDH schemes use fixed block size. However, due to the differences in image complexity, fixed-size blocks have many limitations. Thus far, several methods that break the limitations have been proposed, such as setting a threshold value, and determine the size from the complexity of the block, using sliding window instead of fixed blocks. These methods significantly enhanced the embedding performance of PVO-based RDH schemes, but this can still be improved. The proposed scheme introduces the quad-tree structure, which combines the advantages of several previously proposed methods to design a flexible block patterns, thus fully utilizing the characteristics of the image itself in embedding secret data. Experimental results indicate that the proposed scheme is flexible and better than previous approaches.

Adaptive Reversible Data Hiding Scheme for Digital Images Based on Histogram Shifting

Existing histogram based reversible data hiding schemes use only absolute difference values between the neighboring pixels of a cover image. In these schemes, maxima and minima points at maximum distance are selected in all the blocks of the image which causes shifting of the large number of pixels to embed the secret data. This shifting produces more degradation in the visual quality of the marked image. In this work, the cover image is segmented into blocks, which are classified further into complex and smooth blocks using a threshold value. This threshold value is optimized using firefly algorithm. Simple difference values between the neighboring pixels of complex blocks have been utilized to embed the secret data bits. The closest maxima and minima points in the histogram of the difference blocks are selected so that number of shifted pixels get reduced, which further reduces the distortion in the marked image. Experimental results prove that the proposed scheme has better performance as compared to the existing schemes. The scheme shows minimum distortion and large embedding capacity. Novelty of work is the usage of negative difference values of complex blocks for secret data embedding with the minimal number of pixel shifting.

Image Steganography Based on Foreground Object Generation by Generative Adversarial Networks in Mobile Edge Computing With Internet of Things

Mobile edge computing provides low-latency service computing for the Internet of Things (IoT). Considering the computational cost of high-quality image steganography in practical mobile applications, we believe that mobile edge computing could provide real-time service computing for covert communications. As a mainstream approach to convert communication, image steganographic algorithms prefer to hide secret data in well-textured regions in order to reduce the possibility of being detected. Recently, the generative adversarial networks (GAN) has become one of the most popular architectures for image steganography. However, the GAN-based image steganographic algorithms directly conduct the secret data embedding on the entire cover images and do not sufficiently take the regional texture complexity into account, which will compromise the anti-detection ability. To address this issue, we propose a novel image steganographic algorithm on the generated foreground object region with rich textures. More specifically, the foreground object region is generated onto a given cover image by the GAN, and the secret data is embedded in the foreground object region simultaneously during the generation of the region. The experimental results show that the proposed method can resist steganalysis effectively without significant degradation of image quality and achieve real-time processing.

Stegananalysis of digital images in conditions of varying degrees of contents fullness

An improvement of the steganalytic method for detection of the presence of additional information in color digital images which showed high efficiency in identifying stego formed by embedding of secret data only into one color component of the container is presented. The proposed method analyses digital image in the spatial domain and is based on the accounting of sequential color triads in the matrix of unique colors of the digital content. However, in the process of steganographic transformation cases of embedding of confidential data into two and three color components of images are possible that ensures the concealment of a larger amount of information and requires the improvement of the existing method of steganalysis. In the course of the conducted research the character of perturbations in the quantity of sequential triads of triplets in a matrix of unique colors as a result of embedding of additional information into two and three color components of images originally stored in a losses format was analyzed. Considering obtained results the parameters of the original method for detecting of stego was refined. It has been established that the character of changes in the quantity of sequential triads of triplets as a result of steganographic transformation is different in cases of using containers in a losses format and containers in a lossless format. Based on the obtained data the steganalytic method has been improved by integrating it with the method of detection the fact of compression of digital content developed earlier. The developed method provides high efficiency in detecting stego formed with different degree of container fullness without reducing the accuracy of identifying the filled color components if the additional information was embedded into only one color component of the digital images. This method can be used as a basis for complex steganalysis of digital contents by using existing methods that analyzes color matrixes of images separately.

Data hiding technique in steganography for information security using number theory

In the current era, due to the widespread availability of the Internet, it is extremely easy for people to communicate and share multimedia contents with each other. However, at the same time, secure transfer of personal and copyrighted material has become a critical issue. Consequently, secure means of data transfer are the most urgent need of the time. Steganography is the science and art of protecting the secret data from an unauthorised access. The steganographic approaches conceal secret data into a cover file of type audio, video, text and/or image. The actual challenge in steganography is to achieve high robustness and capacity without bargaining on the imperceptibility of the cover file. In this article, an efficient steganography method is proposed for the transfer of secret data in digital images using number theory. For this purpose, the proposed method represents the cover image using the Fibonacci sequence. The representation of an image in the Fibonacci sequence allows increasing the bit planes from 8-bit to 12-bit planes. The experimental results of the proposed method in comparison with other existing steganographic methods exhibit that our method not only achieves high embedding of secret data but also gives high quality of stego images in terms of peak signal-to-noise ratio (PSNR). Furthermore, the robustness of the technique is also evaluated in the presence of salt and pepper noise attack on the cover images.

Reversible data hiding using Lagrange interpolation for prediction-error expansion embedding

Inspired by reversible data hiding methods that applied the PE (predicted error) strategy will have the advantage of good performances. It means that the closer the PE approaches its climax, the higher embedding capacity and image quality will have. This paper provides four stages of two-phase reversible data hiding method to produce prediction images with Lagrange interpolation on odd and even pixels, and to hide confidential information into the differences between the predicted image and the original image. Lagrange interpolation will be crossly applied on odd and even pixels to produce predicted images, and then histogram shifting modification will be applied to embed secret data into. The experimental results demonstrate the quality of Lena image from this scheme has a PSNR value of 43.97 dB and an embedding capacity of 0.38 bpp, for one level. For enhancing the embedding capacity to 0.98 bpp, our scheme can still maintain a PSNR value of 31.14 dB. From the demonstrated results, it can be obvious to know that our proposed algorithm has superior performances in terms of image quality and embedding capacity than that the algorithms of Ni et al. and Tai et al.

USE OF COLORRGB MODEL AND LSB METHOD FOR STEGANGOGRAPHIC PROTECTION OF INFORMATION IN OFFICE OPEN XML FORMAT FILES

This article represents some aspects of steganographic information protection. The article focuses on an overview of existing methods of hiding information, especially that allow you to embed hidden data into a text file. To create a software tool, the authors chose the LSB method. The preferred method uses the RGB color model for effectively hiding information in the OFFICE OPEN XML format files.The principle of the LSB method (Least Significant Bit) is replacing the least significant bits of the container (audio, video file, image or text file) with the bits of the message. The possibilities of the human eye are limited in distinguishing the shades of the same color. That is why this substitution is imperceptible to the human.This method can be used while developing an algorithm for embedding secret data into a container. We have a hidden message in the *.docx document. The document isn’t empty. The amount of data that we can fulfill depends on the amount of the information. The more text the report contains, the more data we can hide there. We add the data itself to the RGB color channels of each text character from the file. First, we need extract from the Word document all the necessary data. The text and information about the colors of each character in the RGB format. Then the resulting color components need to be converted into a binary number system and replace the younger bits of the component colors with the bits of our message.The software tool that implements the described algorithm is developed at the Department of «Software Systems» of theDneprovskiyStateTechnicalUniversity. Also, it is created its own docx documents parser that fully satisfies the requirements of the task and contains only the necessary functions, such as reading text with preservation of formatting, reading the color of the characters used in the file, etc.

Reversible data hiding using the dynamic block-partition strategy and pixel-value-ordering

The reversible watermarking algorithm based on pixel value ordering (PVO) embeds secret data by modifying the maximum and minimum values in a pixel block. The performance of this algorithm heavily depends on the inherent correlation among adjacent pixels within an image block. To improve the inherent correlation among adjacent pixels within an image block, a new method to incorporate the dynamic block-partition strategy into the PVO algorithm is proposed in this paper. This new method includes the following procedure: First, the host image is divided into non-overlapping regions according to the image pixel values; then, each region is partitioned into different blocks, which are subsequently classified according to the local complexity and predefined threshold values for embedding; and finally, watermark embedding is performed using the PVO-based algorithm. In the proposed method, the pixel values of each embedded block are located in a relatively small region to improve the inherent correlation and thereby enhance the embedding performance of PVO. The experimental results show that the proposed algorithm has a better embedding performance compared with that of the conventional PVO based algorithm.

High Embedding Capacity Data Hiding Algorithm for H.264/AVC Video Sequences without Intraframe Distortion Drift

Data hiding is a technique that allows secret data to be delivered securely by embedding the data into cover digital media. In this paper, we propose a new data hiding algorithm for H.264/advanced video coding (AVC) of video sequences with high embedding capacity. In the proposed scheme, to embed secret data into the quantized discrete cosine transform (QDCT) coefficients of I frames without any intraframe distortion drift, some embeddable coefficient pairs are selected in each block, and they are divided into two different groups, i.e., the embedding group and the averting group. The embedding group is used to carry the secret data, and the averting group is used to prevent distortion drift in the adjacent blocks. The experimental results show that the proposed scheme can avoid intraframe distortion drift and guarantee low distortion of video sequences. In addition, the proposed scheme provides enhanced embedding capacity compared to previous schemes. Moreover, the embedded secret data can be extracted completely without the requirement of the original secret data.

High payload image steganography based on Laplacian of Gaussian (LoG) edge detector

Abstract Image Steganography is the method of concealing secret information into the digital image, and LSB replacement policy is recognized as the foremost and widely used approach. In traditional LSB based scheme, the secret bits are fabricated into the LSB position of each pixel without making a prior analysis of the image contents. As a consequence, the visual quality as well as the security of the stego-image becomes a concern even to achieve a low embedding rate. In this paper, the embedding of secret data has been made by classifying the pixels of the cover image into following two categories: edge and non-edge. This classification is made by applying the Laplacian of Gaussian (LoG) edge detector over the gray-scale images. It has been observed that the non-edge pixels get affected severely compared to edge pixels at higher embedding rate and therefore, more bits are embedded in edge pixels rather than in the non-edge pixels. The disadvantage of existing edge detection based Steganography schemes is the embedding of (extra) edge information besides the actual embedding. Unlikely, the proposed scheme proficiently avoids the burden of embedding of extra edge information and utilizes the embedding space fully. Experimental results ensure that the proposed scheme achieves higher payload and better stego-image quality compared to existing schemes.

An Efficient Reversible Data Hiding Scheme for Encrypted Images

Reversible data hiding in the encrypted domain is an emerging technology, as it can preserve the confidentiality. In this article, an efficient method of reversible data hiding in encrypted images is proposed. The cover image is first partitioned into non-overlapping blocks. A specific modulo addition operation and block-scrambling operation are applied to obtain the encrypted image. The data-hider, who does not know the original image content, may reversibly embed secret data based on the homomorphic property of the cryptosystem. A scale factor is utilized for selecting embedding zone, which is scalable for different capacity requirements. At the receiving end, the additional data can be extracted if the receiver has the data-hiding key only. If the receiver has the encryption key only, he/she can recover the original image approximately. If the receiver has both the data-hiding key and the encryption key, he can extract the additional data and recover the original content without any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.

Role of Soft Computing Techniques in Improving the Strength of Steganographic Systems

In recent times steganographic systems that deal with concealing of secret data inside images have gained much attention. Robustness, capacity of embedding and imperceptibility are the major issues concerning embedding of secret data inside a cover. This paper analyses the recent advancements in this field by combining the soft computing techniques with steganographic algorithms for increasing the robustness, capacity and imperceptibility of the images used for embedding.

A network steganographic approach to overlay cognitive radio systems utilizing systematic coding

Network steganography is an information hiding technique that utilizes network protocols to facilitate hidden communication. The aim is to embed secret information bits into regular network traffic (as a carrier) so that confidential data can be transmitted covertly between two communicating parties. In this paper, the concept of network steganography is extended for overlay cognitive radio networks utilizing cooperative relaying protocols with systematic channel codes. In the considered model, the cognitive node relays the primary data according to a time-slotted decode-and-forward cooperative protocol with maximum-ratio combining (MRC) at the primary destination. We propose a steganographic approach in which the cognitive node embeds confidential cognitive data at the wavelet transform domain into primary data code words. In this approach, the embedding operation is designed to preserve the statistical properties of the cover data in terms of decoded BER after MRC decoding of code words at the destination node which includes both the effect of wireless channel errors and errors due to embedding distortion. From this point of view, the proposed scheme may be seen as a lossless steganography scheme that embeds secret data into coded data strings. We provided implementation examples using both systematic BCH and turbo channel coding. The results show that the proposed scheme can provide diversity gain using stego-based MRC at the primary receiver and covert confidential cognitive data communications simultaneously.

Separable Reversible Data Hiding in Encrypted Images Based on Two-Dimensional Histogram Modification

An efficient method of completely separable reversible data hiding in encrypted images is proposed. The cover image is first partitioned into nonoverlapping blocks and specific encryption is applied to obtain the encrypted image. Then, image difference in the encrypted domain can be calculated based on the homomorphic property of the cryptosystem. The data hider, who does not know the original image content, may reversibly embed secret data into image difference based on two-dimensional difference histogram modification. Data extraction is completely separable from image decryption; that is, data extraction can be done either in the encrypted domain or in the decrypted domain, so that it can be applied to different application scenarios. In addition, data extraction and image recovery are free of any error. Experimental results demonstrate the feasibility and efficiency of the proposed scheme.