Embedding Phase Research Articles

A New Method of Coding for Steganography Based on LSB Matching Revisited

LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this method works only for n = 2 , where n is the number of bits in a block of the secret message. In this paper, we propose an improved version of the LSB matching revisited approach, which works for n > 2 . The proposed scheme contains two phases including embedding and extracting the message. In the embedding phase, we first convert the secret message into a bit-stream, and then the bit-stream is divided into a set of blocks including n bits in each block. Then we choose 2 n − 1 pixels for hiding such n bits of the secret message. In the next step, we choose the operations needed to generate such a message. Finally, we perform the obtained operations over the coefficients to hide the secret message. The proposed approach needs fewer changes than LSB MR when n > 2 . The capacity of the proposed approach is 2 n − 1 / 2 n − 1 − 1 × 100 % higher than the F5 method where this value for n > 2 is bigger than 75%. For example, the capacity of our scheme is 75% higher than the capacity of F5 for n = 3 . The proposed method can be used in the first step of every steganography method to reduce the change in the stego image. Therefore, this method is a new coding method for steganography. Our experimental results using steganalysis show that using our method provides around 10% higher detection error for SRNet over two steganography schemes.

Smart Nanocomposite Nonwoven Wearable Fabrics Embedding Phase Change Materials for Highly Efficient Energy Conversion-Storage and Use as a Stretchable Conductor.

Flexible and intelligent electronics are highly demanded in wearable devices and systems, but it is still challenging to fabricate conductive textiles with good stretchability, multifunctionality, and responsiveness to multistimuli. Therefore, kinds of smart conductive fabrics with high stretchability and thermal properties, good washability, excellent shape stability, rapid responsiveness to external stimuli (e.g., electrical and photonic), and outstanding energy conversion and storage properties were designed and prepared. The nonwoven smart fabrics were fabricated by electrospinning of a solution of multiwalled carbon nanotubes (MWCNTs)/lauric acid (LA)/thermoplastic polyurethane (PU) and dip-coating conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS) on the obtained nanofibers. The smart textiles showed tunable temperature and phase change enthalpy that responded to external stimuli such as electrical voltage, infrared light, and sunlight. At the same time, they realized the storage and conversion of energy reversibly with a high efficiency. The elastic fabrics could also be used as a stretchable conductor in a range of deformation. The integrative functions of the smart fabrics promise them great potential in wearable systems and intelligent protective garments.

CPA-Secure Privacy-Preserving Reversible Data Hiding for JPEG Images

The Encrypted Image Reversible Data Hiding (EIRDH) is a hot area of research in multimedia outsourcing scenarios. In such a setting, a content owner possesses confidential images that he wants to upload to an untrusted server. The server is supposed to embed a secret message in the images before sending them to potential receivers, and the receivers expect to recover the original images without any distortion. EIRDH schemes are designed to meet reversible data hiding goals while preserving the confidentiality of the host images. Confidentiality is provided by means of encryption algorithms; however, these algorithms, in turn, introduce the challenge of dealing with ciphered images in both embedding and extraction phases. The current paper tries to propose a privacy-preserving reversible data hiding scheme for JPEG images without the need for any levels of decompression. We propose an elliptic curve-based asymmetric, commutative, and separable EIRDH method, in which no entities other than the sender and the eligible receiver of the hidden message (embedded in the encrypted image) are able to recognize its existence. In particular, even the server that performs the embedding remains completely unaware of the content of the images. An important security feature of our scheme involves the security of its multiple encryptions against Chosen-Plaintext Attack (CPA), which is an attack model that assumes the adversary can obtain the encryptions of the images on his choice to achieve possible extra information to attack. Experimental results show that our scheme achieves full reversibility and a satisfactory level of capacity, while it accurately extracts all the hidden bits.

Improving the Hot Corrosion Resistance of Nanostructured ZrO2-7wt.%Y2O3 Thermal Barrier Coatings Fabricated by Plasma Spraying

Conventional and nanostructured ZrO2-7wt.%Y2O3 thermal barrier coatings (TBCs) were prepared by plasma spraying technology. Microstructure and hot corrosion resistance of two TBCs in 75%Na2SO4+25%NaCl (mass fraction) mixed molten salt under 850 °C were compared. Meanwhile, hot corrosion failure mechanisms of TBCs were investigated. Results demonstrated that both conventional and nanostructured TBCs were typical lamellar stacking characteristic. However, compared with conventional TBC, the nanostructured TBC presented the base phase which is gained from recrystalization of fully melted nano-particles as well as the embedding phase of partially melted nano-particles. The nanostructured TBC has lower porosity and higher density. For both conventional and nanostructured TBCs, hot corrosion failure is caused by partial transformation of tetragonal phase (t-ZrO2) into monoclinic-phase (m-ZrO2) martensite as a response to the consumption of the stabilizer Y2O3. However, the nanostructured TBC generally has lower degree of hot corrosion and better protection to the metal bonding layer and matrix compared with conventional TBC.

RETRACTED ARTICLE: An effective secret image sharing using quantum logic and GPGPU based EDNN super-resolution

This paper presented an effective secret image sharing with super-resolution utilizing quantum logic and enthalpy based adaptive deep neural network. The proposed technique is processed as; at the sender side, initially secret input image is converted into a halftone image format by utilizing Error diffusion with varying thresholds (EDVT) method. Then in share generation phase, shares are produced with the basis matrix. Here, the basis matrix is created utilizing the quantum logic methodology. Then in embedding phase, discrete wavelet transform (DWT) is utilized for encoding shares. At the receiver side, encoded image is reconstructed using XOR operation and results the low-resolution image. Finally, enthalpy based adaptive deep neural network (EDNN) is designed with the General Purpose Graphic Processing Unit (GPGPU) to enhance the resolution of the reconstructed images and to lessen the time complexity of deep learning. Here, the EDNN is adapted with the enthalpy based normalization to mitigate the over fitting in layers of deep neural network. Furthermore, the proficiency of the proposed work improved in terms of normalized cross correlation, normalized absolute error, peak signal to noise ratio, mean square error and execution time by deploying images among CPU and GPGPU in an enhanced manner.

Dual embedding model: a new framework for visually meaningful image encryption

Visually meaningful image encryption (VMIE) means that a plain image is transformed into a visually meaningful cipher image which makes the plain image more imperceptible than the noise-like cipher image generated by traditional image encryption algorithms. In essence, existing VMIE algorithms exploit the idea of information steganography, i.e., embedding a secret into a host image to generate a cipher image which is visually similar to the original host image. However, it is well known that steganalysis technique is a fatal threat to steganography. Therefore, the security of existing VMIE algorithms will be potentially threatened by steganalysis technique. To improve the security of VMIE algorithms, we propose a new VMIE framework with dual embedding model. In the new framework an additional embedding phase is added. More specifically, in the first embedding process, the pre-encrypted image is embedded into the reference image to generate a visually meaningful reference cipher image. In the second embedding process, the difference between the visually meaningful reference cipher image and the original reference image is calculated to obtain a deviation matrix. Then, the deviation matrix is used as the disguised information and then embedded into the disguised host image to obtain a disguised visually meaningful encrypted image. The reference image can be any image with specified size thus ensuring the security of the VMIE algorithm. To verify the validity of the proposed VMIE framework, an example algorithm is proposed. Simulation results and performance analyses show that the example algorithm has a high time efficiency, high robustness and security.

A digital watermarking method based on NSCT transform and hybrid evolutionary algorithms with neural networks

This study aims to determine the watermark resistance to different attacks as well as the PSNR level, both of which are essential requirements of watermarking. In our research, we came up with an intelligent design based on NSCT-SVD that fulfills these requirements to a great extent and we managed to use different-sized images for watermark instead of using logos on the host images. Yet we were able to improve PSNR levels and resistance to various attacks. In this paper an NSCT-SVD-based smart watermark model is proposed. We first compare the PSO and PSO-GA algorithms for greater stability using larger SFs obtained by the PSO-GA-AI algorithm. The resulting host image is then decomposed by NSCT transform to obtain images below the low frequency range. Stationary Wavelet Transform (SWT) is performed once on these coefficients and the low frequency coefficients are fed to SVD. Afterwards, SWT transform is performed on the watermark image and the transform is once again taken from the HL coefficients and the LL frequencies are given to the SVD conversion. The rest of image process is insertion. This insertion process dramatically increases the visual transparency and PSNR value. The experiment shows that such a model is able to resist the repeated image attacks with better visibility and power. These results are compared before and after using SWT. We have used a PSO-based algorithm for better results on the False Positive rate in the embedding phase.

An enhanced LSB-based quantum audio watermarking scheme for nano communication networks

In recent years, digital multimedia including image, audio, and video are extended to quantum computation and quantum networks. Consequently, copyright protection of digital multimedia in quantum networks becomes a significant issue. As an important security technology, quantum watermarking is an appropriate solution, which embeds copyright information into the carrier signal. This work presents an enhanced least significant bit (LSB) based audio watermarking using reflected gray code. In the presented scheme, the watermark image is first scrambled using a new scrambling method presented in this paper, which modifies pixel values for scrambling instead of changing pixel positions. The scrambled image is then converted into a qubit sequence to comply with one-dimension audio signal, and the qubits are embedded into carrier quantum audio signal using an embedding key. In embedding phase, every four low qubit of target audio sample replaced with their nearest even or odd number in reflected gray code, based on the value of embedded qubit. For every procedure of the proposed scheme, the quantum circuit and complexity analysis is presented. Experimental results prove that the proposed scheme has good transparency, capacity and security.

Reversible Fragile Watermarking for Multichannel Images with High Redundancy Channels

The paper presents a methodology to protect the integrity of multichannel images, having some highly redundant channels, by means of a reversible fragile watermarking algorithm. The watermark embedding phase uses a lossless compression method to compress the high redundancy channels, stores the compressed stream into their most significant bits, then embeds a secret fragile watermark by modifying the least significant bits of the high redundancy channels. In case the watermarked image is not modified, the host image can be perfectly reconstructed; otherwise, the modified area can be detected and located with very high probability and the area that has not been forged can be restored as in the original host image. The embedding of the watermark is performed by a Genetic Algorithm in the Karhunen-Loève Transform (KLT) domain: the use of a secret space defined by the KLT guarantees both security of the method and a high sensitivity in the detection of the forged areas.

A separable reversible data hiding scheme for encrypted images based on Tromino scrambling and adaptive pixel value ordering

To further improve capacity and reduce distortion, a novel separable reversible data hiding (RDH) scheme for encrypted images based on Tromino scrambling and adaptive pixel value ordering (PVO) is proposed. An image is first partitioned into non-overlapped blocks with three pixels in L shape, and then Tromino scrambling and stream encryption are performed to the blocks in sequence. In the embedding phase, an adaptive pixel value ordering (PVO) scheme is utilized. The differences between the smallest pixel value and the rest two pixel values are calculated, and the pairwise prediction errors corresponding to each block is accumulated to form a two-dimensional prediction error histogram. Subsequently, an adaptive 2D histogram mapping is established for reversible data hiding. Experimental results and analysis show that it is separable and can completely recover the original image. Furthermore, compared with other PVO, the adaptive PVO makes better use of the features of the images after Tromino encryption, it can achieve larger capacity and better visual quality of the decrypted images compared with the existing methods.

Comparative study of solar hot air heating systems with phase change materials in plateau areas

Rich solar energy resources in plateau areas of Western China are suitable for local heating. However, common solar heating systems face the potential hazard and maintenance difficulties caused by climatic conditions. In this paper, the solar hot air heating system using the air medium evacuated tube collectors (ETCs) with embedding phase change materials (PCM) was discussed, which can be a good solution in plateau areas. The whole system model was built in TRNSYS software and validated with practical data. Then the comparative study was conducted to evaluate the energy-efficiency performance and feasibility of six kinds of solar heating systems, which also involved the fully electric heating, based on the three thermal types of buildings in Lhasa. It was concluded that the solar hot air heating system is the most suitable application in plateau areas, which shifts more solar energy to night time heating and requires less maintenance. Furthermore, the influence of parameters on the system performance was also investigated, such as collector area, buffer tank volume and electric power. This study will help the design and application of solar hot air heating system with PCM in plateau areas for winter heating.

A novel chaos-based approach in conjunction with MR-SVD and pairing function for generating visually meaningful cipher images

For secure transmission of digital images, existing cryptographic algorithms transform images into a noise-like appearance. One obvious inference that an adversary could draw is that the noise-like texture is a cipher, prompting to apply classical cryptanalysis. This article proposes an efficient algorithm that produces a visually coherent and meaningful cipher image to bypass the cryptanalysis. In the partial-encryption phase, the Arnold-3D map drives the permutation mechanism, whereas the implementation of the diffusion phase is done by harnessing the iterates of the chaotic Logistic map. The partial cipher is compressed using a Cantor-like pairing function that does a 4 to 1 pixel encoding to facilitate embedding. The embedding phase is implemented in the spatial domain by applying Multi-resolution singular value decomposition on the reference image and replacing the vertical, horizontal, diagonal sub-band with the encoded cipher. The encoding of pixels facilitates the transmission of the visually meaningful cipher image to be of the same size as the original image rather than four-times the original image as reported in earlier schemes. Simulation results confirm the security of the scheme.

A secure communication approach in OFDM using optimized interesting region-based video watermarking

PurposeThe technique for hiding confidential data in specific digital media by enhancing the graphical contents is known as watermarking. The dissemination of information over a secure channel is essential for multimedia applications. The purpose of this study is to develop a secure communication approach for OFDM system.Design/methodology/approachThis paper exploits a secure communication in the orthogonal frequency division multiplexing (OFDM) system using wavelet-based video watermarking technique. In this work, the Chronological-MS algorithm is used for securing the data communication in the OFDM system. Here, the secret message is embedded in video frames using wavelet transform for hiding sensitive information and the hidden information is transmitted over the OFDM system. The Chronological-MS algorithm is used for selecting the optimal regions in the video for embedding secret message. In embedding phase, wavelet coefficients are obtained by applying wavelet transform on the frame for embedding the secret message. Meanwhile, in extraction phase, the inverse wavelet transform is applied to extract the secret message.FindingsConsidering number of frames, the maximum Peak signal-to-noise ratio (PSNR) value is attained by proposed Wavelet + Chronological MS method for Video 2 with value 73.643 dB, respectively. Meanwhile, the minimum mean squared error (MSE) attained by the proposed Wavelet + Chronological MS method is when considering number of frames with MSE values as 0.001 for both Videos 1 and 2. The minimum bit error rate (BER) value is attained by the proposed method with value 0.00009 considering random noise with Video 1. Thus, the proposed Wavelet + Chronological MS have shown better results than the existing techniques.Originality/valueThis work proposes a wavelet-based watermarking method using Chronological-MS, for initiating secured communication over an OFDM. One of the main advantages of wavelets is that they offer a simultaneous localization in time and frequency domain. Hence, the proposed method offers the highly secured data transmission over the OFDM.

A general framework for partial reversible data hiding using hamming code

A general framework for partial reversible data hiding is proposed in this paper. The original image is adjusted to form a cover image in image transferring phase. The minimal square error criterion between Hamming codeword and the bits from the original image is adopted to generate the cover image. After image transformation, some bits in the cover image are actually a Hamming codeword. In data embedding phase, the secret bits are concealed into the cover image to generate a stego image. The secret messages can be extracted from the stego image, and the stego image can be recovered back to cover image in data extraction and image restoration phase. The so-called partial reversible property indicates an almost distortion-free original image (e.g., cover image) can be obtained. Theoretical analysis on the embedding capacity and visual performance by the proposed method is given. Further, experimental and theoretical results are demonstrated to show the feasibility and advantages of the proposed method.

A robust digital image watermarking scheme based on bat algorithm optimization and SURF detector in SWT domain

This paper presents an optimized robust digital image watermarking scheme based on Stationary Wavelet Transform (SWT) using Bat optimization Algorithm (BA) and Speed-Up Robust Feature (SURF). The proposed scheme applies high-frequency coefficients of the SWT of the host image in the BA framework to optimize watermark strength factors in the embedding process, considering relevant attacks. On the final step of this process, the SURF detector is employed on the watermarked image for getting point features used for geometric distortion correction. For watermark extracting, the primary step is to correct probable geometrical distortions, utilizing the SURF rotation and scaling invariance property, and the procedure goes on by executing the reverse of embedding phase steps. For evaluating the capabilities of the proposed algorithm, different types of image processing operations such as Gaussian filtering, scaling, rotation and salt and pepper, Poison, speckle, and Gaussian noise, have been used as attacks. According to the experimental results, the proposed combination of techniques exhibits an overall superior performance in both imperceptibility and robustness metrics in various situations compared to state-of-the-art and relevant methods.

Pixel Prediction-Based Image Steganography by Support Vector Neural Network

Abstract Securing the privacy of the medical information through the image steganography process has gained more research interest nowadays to protect the privacy of the patient. In the existing works, least significant bit (LSB) replacement strategy was most popularly used to hide the sensitive contents. Here, every pixel was replaced for achieving higher privacy, but it increased the complexity. This work introduces a novel pixel prediction scheme-based image steganography to overcome the complexity issues prevailing in the existing works. In the proposed pixel prediction scheme, the support vector neural network (SVNN) classifier is utilized for the construction of a prediction map, which identifies the suitable pixels for the embedding process. Then, in the embedding phase, wavelet coefficients are extracted from the medical image based on discrete wavelet transform (DWT) and embedding strength, and the secret message is embedded into the HL wavelet band. Finally, the secret message is extracted from the medical image on applying the DWT. The experimentation of the proposed pixel prediction scheme is done by utilizing the medical images from the BRATS database. The proposed pixel prediction scheme has achieved high performance with the values of 48.558 dB, 0.50009 and 0.9879 for the peak signal to noise ratio (PSNR), Structural Similarity Index (SSIM) and correlation factor, respectively.

An improved visually meaningful encrypted image scheme

An encrypted image generally presents an appearance of texture-like or noise-like image, which exhibits an indication of encrypted data that may motivate a significantly large number of attacks. To address this problem several approaches have been carried out, where an encrypted image is transformed into a visually meaningful encrypted image (VMEI). We present an improved approach to encrypt a plain image into a visually meaningful cover image, where the preprocessing and embedding phases are modified to achieve a quite comparable performance. To make the assessment of this proposal, some standard metrics such as PSNR and SSIM are performed, and the obtained numerical results show that this proposal is comparable or superior to some VMEI schemes used as benchmark in this work. In most of the reference images considered in the dataset the values of PSNR are greater than 40 dB, and a value close to 1 for the SSIM metric, which means a great similarity and high quality, respectively, between the reference images and their obtained VMEI images. Also, the two-dimensional detrended fluctuation analysis is carried out to observe the scaling behavior of the images, which allows us to have a perceptual security parameter of encrypted images and visually meaningful cover images. For this metric, the scaling exponent values of the VMEI images are close to 2.1, which are very similar to the values obtained for the reference images, a situation that confirms that the hidden information may not be detected by the human visual system. Furthermore, for two reference images, this metric was able to detect how the pixel values are distributed, and how the pixel values are highly correlated, suggesting that this metric can be an objective measure of encrypted images.

Experimental investigation of the performance of thermal energy storage with embedded phase change materials as wall insulator

Thermal energy storage (TES) has been widely adopted to bridge the mismatch between energy supply and demand. In general, thermal energy storage is segregated as sensible TES and latent TES whereby both have their own advantages and disadvantages. This study explores the possibility of utilizing the advantages of both sensible and latent TES by embedding phase change materials as a wall of the sensible TES. To investigate the performance of the proposed TES, an experimental set-up of TES with PCM embedded in the wall is developed. Temperature distribution within TES is measured and recorded during charging and discharging process. Several key parameters are evaluated to gauge their influence on the performance of the studied TES. The results indicate that the performance of TES with embedded PCM is superior that that without PCM, indicating the potential of the proposed design for high performance thermal energy storage application.

Importance of osteocyte-mediated regulation of bone remodelling in inflammatory bone disease.

Although the impact of osteoblast-osteoclast crosstalk in bone remodelling has been intensively studied, the importance of osteocytes, descendants of osteoblasts, in this process has for a long time been neglected. During their embedding phase, osteocytes undergo considerable phenotypic transformation, from a cuboidal, highly metabolically active osteoblast secreting extracellular matrix to a small, stellate, quiescent osteocyte with numerous long dendrites. Osteocytes are encysted in cavities (lacunae) and their dendritic extensions are located in tunnels (canaliculi) forming a remarkable, highly branched, lacunar-canalicular signalling network that spans the entire bone matrix. Osteocytes and their dendrites can communicate directly with each other and through the release of effector proteins such as sclerostin and nuclear factor κB ligand (RANKL), influence osteoblast and osteoclast formation. This allows osteocytes embedded within the bone matrix to communicate and coordinate activity of cells on the bone surface to adapt to mechanical needs and hormonal changes. Besides their importance in sustaining physiological bone homeostasis, accumulating evidence suggests that dysregulated osteocyte function and alterations in the osteocyte lacunar-canalicular network structure are characteristics of skeletal diseases. This review highlights some aspects of osteocyte communication with osteoclasts and mesenchymal stromal cells, the importance of blood vessel-osteocyte interaction and describes central functions of these cells in rheumatoid arthritis, osteoarthritis, osteomyelitis and osteoporosis. Within the last decade new technologies and tools have facilitated the study of osteocyte biology and the search for therapeutic targets to address bone fragility in the near future.

A novel chaotic steganography method with three approaches for color and grayscale images based on FIS and DCT with flexible capacity

In this paper, a new chaotic steganography method based on Fuzzy Inference System (FIS), using Discrete Cosine Transform (DCT) on color and grayscale images is proposed. The proposed algorithm is designed in three different approaches to have important factors of robustness, imperceptibility, and transparency with respect to applications. In order to achieve this goal, important parameters in the Human Visual System (HVS), such as texture and luminance, using DCT coefficients are computed. For more precision and flexibility in selecting host blocks for embedding, FIS system is used. Due to the importance of robustness and transparency in different applications, the best target host blocks are intelligently determined using the degree defined in the fuzzy system. This flexibility greatly enhances the efficiency of the algorithm in various using goals. One of the outstanding aspects of the proposed method is error controlling with increasing capacity. At first, embedding is done on middle frequency (MF) then to increase the capacity, coefficients in high frequency are also considered with two different zigzag scanning directions in selection, middle to high (MHF) and high to middle (HMF). The ordering selection of different color channels (for color image), blocks, coefficients in embedding phase, and encryption algorithm of secret message are done by chaotic sequences which has a positive impact on security level. Providing an efficient integration technique (synchronization) in the number of coefficients of each block leads to increasing the security of the proposed method. One of best novelty which causes decreasing bit error rate (BER) beside increasing capacity, is approximating of the distortion during DCT and IDCT operations in embedding phase. The experimental results demonstrate that high level of transparency and robustness for MF, and if more capacity is needed, although both algorithms HMF and MHF have desirable results, but HMF provides higher level of transparency and MHF more robustness against noises and attacks which can be used with respect to applications.