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The edge area of an image is more resilient to distortion caused by embedding in steganography, driving the advancement of edge detection-based methods. State-of-the-art techniques, including hybrid, dilation, and Fuzzy-based approaches, have been developed to enhance steganography performance. Typically, these methods categorize image pixels into two regions: edge and non-edge areas. This research introduces graded Fuzzy edge detection, classifying pixels into main, supporting, and non-edge categories. Consequently, the embedding priority and message bit determination become more diverse and adaptive. Experimental results demonstrate that graded Fuzzy edge detection optimizes imperceptibility while preserving security and capacity. This technique is combined with various steganographic and reversible data hiding (RDH) methods, exhibiting improvements in stego image quality with over 1dB enhancement based on PSNR, as well as maintaining payload capacity and security aspects according to RS and PDH steganalysis. [ABSTRACT FROM AUTHOR]

In the current distributed environment, reversible data hiding in encrypted domain (RDH-ED) cannot grant corresponding privileges according to users' identity classes. To address this issue, this paper proposes a hierarchical authorization structure embedding scheme based on secret image sharing (SIS) and users' hierarchical identities. In the first embedding, the polynomial coefficient redundancy generated in the encryption process of the SIS is utilized by the image owner. For the second, the participants are categorized into two parts. One is core users with adaptive difference reservation embedding, and the other is ordinary users with pixel bit replacement embedding. At the time of reconstruction, more than one core user must provide pixel differences, which grants more privileges to core users. The experimental results demonstrate that the average embedding rate (ER) of the test images is 4.3333 bits per pixel (bpp) in the (3, 4) threshold scheme. Additionally, the reconstructed image achieves a PSNR of +∞ and an SSIM of 1. Compared to existing high-performance RDH-ED schemes based on secret sharing, the proposed scheme with a larger ER maintains strong security and reversibility. Moreover, it is also suitable for multiple embeddings involving multilevel participant identities. In conclusion, the results underscore the efficacy of our technique in achieving both security and performance objectives within a complex distributed setting. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) is an advanced data protection technology that allows the embedding of additional information into an original digital medium while maintaining its integrity. Color images are typical carriers for information because of their rich data content, making them suitable for data embedding. Compared to grayscale images, color images with their three color channels (RGB) enhance data embedding capabilities while increasing algorithmic complexity. When implementing RDH in color images, researchers often exploit the inter-channel correlation to enhance embedding efficiency and minimize the impact on image visual quality. This paper proposes a novel RDH method for color images based on inter-channel correlation modeling and improved skewed histogram shifting. Initially, we construct an inter-channel correlation model based on the relationship among the RGB channels. Subsequently, an extended method for calculating the local complexity of pixels is proposed. Then, we adaptively select the pixel prediction context and design three types of extreme predictors. The improved skewed histogram shifting method is utilized for data embedding and extraction. Finally, experiments conducted on the USC-SIPI and Kodak datasets validate the superiority of our proposed method in terms of image fidelity. [ABSTRACT FROM AUTHOR]

Pixel value ordering (PVO) and prediction error expansion (PEE) techniques are now being combined for improved performance in the domain of reversible data hiding (RDH). Conventional PVO can only embed two data bits in a smooth picture block in a row or column, which is insufficient to meet the contemporary demands of much payload in RDH. There is a lot of room to enhance the bit stuffing by inserting more than two data bits in a smooth block while maintaining acceptable visual image quality and data security. In this study, we suggest a context pixel-based data concealing strategy based on PVO combined with PEE, in which each block can insert two or more data bits. This proposed approach has three distinct features: smooth block selection, minimum and maximum position selection, and pixel difference with median value for data embedding. Furthermore, more than two pixels can be used to embed the secret data bit. The block is recommended by the selection of the neighbouring and present block's pixel. The use of context pixels in context pixel-based PVO (CPPVO) improves both embedding efficiency and picture quality. When the block size is Z = (3 × 3) , the average embedding capacity (EC) of our novel approach is over 70,000 bits, and the average PSNR is over 40 dB. The results of the experiments reveal that our technique is more dependable than other state-of-the-art systems in terms of security, picture quality, and secret volume. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) is a technique that embeds secret data into digital media while preserving the integrity of the original media and the secret data. RDH has a wide range of application scenarios in industrial image processing, such as intellectual property protection and data integrity verification. However, with the increasing prevalence of color images in industrial applications, traditional RDH methods for grayscale images are inadequate to meet the requirements of image fidelity. This paper proposes an RDH method for color images based on channel reference mapping (CRM) and adaptive pixel prediction. Initially, the CRM mode for a color image is established based on the pixel variation correlation between the RGB channels. Then, the pixel local complexity context is adaptively selected using the CRM mode. Next, each pixel value is adaptively predicted based on the features and characteristics of adjacent pixels and reference channels, and then data is embedded by expanding the prediction error. Finally, we compare seven existing RDH algorithms on the standard image dataset and the Kodak dataset to validate the advantages of our method. The experimental results demonstrate that our approach achieves average peak signal-to-noise ratio (PSNR) values of 63.61 and 60.53 dB when embedding 20,000 and 40,000 bits of data, respectively. These PSNR values surpass those of other RDH methods. These findings indicate that our method can effectively preserve the visual quality of images even under high embedding capacities. [ABSTRACT FROM AUTHOR]

Multi-party reversible data hiding over ciphered images (MRDH-CI) has high restorability since the image is split into multiple ciphered images by secret sharing. However, the MRDH-CI methods either fail to produce satisfied results, or only work well for conventional images. This paper introduces a multi-party reversible data-hiding approach over ciphered overexposed images. First, the pixels of the overexposed images are decomposed into two parts, each of which can be used for secret sharing. Then, the decomposed overexposed images are converted into multiple ciphered overexposed images by using a modified secret sharing method, in which the differences of the ciphered overexposed images are retained. The symmetry of the difference retaining makes the secret data conceal within the ciphered overexposed images such that the marked ciphered overexposed images can be created. Finally, by collecting sufficient marked ciphered overexposed images, it is possible to symmetrically reconstruct the concealed data and primitive overexposed image. Experimental results illustrate that the presented method can efficiently deal with overexposed images while maintaining a low computational overhead. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) is a special class of steganography that is capable of recovering the original cover image upon the extraction of the secret data. The main goal of this paper is to develop different adaptive predictors based on superpixel irregular block sorting. Firstly, a superpixel irregular block and sorting strategy is proposed which is applied to histogram shifting for the first time. Then, a multi-directional edge classification method is proposed, which divides pixels into strong edge pixels, normal edge pixels, and weak edge pixels. Moreover, strong edge pixels and normal edge pixels are further divided into four directions. According to edge classification, the most appropriate adaptive multi-predictor is proposed. Finally, an optimization-based data hiding strategy is proposed. The proposed scheme focuses on constructing a sharp enough histogram. The investigational results demonstrate that the proposed scheme achieves large capacity, high image quality, and low complexity. [ABSTRACT FROM AUTHOR]

In prediction error-based reversible data hiding, multiple histograms modification (MHM) is well known for high image quality and thus has received wide attention in recent years. However, the computational cost for performance optimization in MHM is too high, which is particularly critical for real-time applications. This manuscript aims to reduce the computational complexity of MHM by presenting two techniques, including fast performance optimization and adaptive pixel distribution. Fast performance optimization provides a two-stage process for optimal bin selection by exploiting the concept of per-bit distortion of data embedding within a prediction error histogram (PEH). In fast performance optimization, the distribution characteristics of the per-bit distortion are investigated to significantly narrow down the solution space of optimal bin selection. The second technique is adaptive pixel distribution, which tries to nonuniformly allocate pixels into multiple PEHs to further reduce the time complexity. Extensive experiments show that the computational complexity of MHM is significantly reduced while well preserving the image quality. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Ordnance Equipment Engineering is the property of Chongqing University of Technology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the Improved Pixel Value Ordering (IPVO) reversible data hiding method first, a block of n pixels is sorted in ascending order. Then two pixel-pairs are established from the first two pixels and the last two pixels of the sorted block to embed at most two data bits. This paper uses the first three pixels and the last three pixels of the sorted block to form four pixel pairs for embedding at most four data bits. In fact, on the right, using the IPVO technique to embed data bits in the pair of (n − 2)−th and (n − 1)−th pixels and the pair of (n − 1)−th and n−th pixels. Embedding data bits in two pairs of pixels on the left is done similarly. The pixel pairs here all consist of two consecutive pixels in a sorted pixel block, so the embedding efficiency is high. Compared with IPVO-method, the proposed method has doubled the number of pixel pairs used, and the embedding capacity increased from 1.5 to 1.9 times depending on the smoothness of the original images. The experiment results are shown that the proposed method has a superior embedding capacity compared to the existing Pixel Value Ordering(PVO)-based reversible data hiding methods while maintaining good stego image quality. [ABSTRACT FROM AUTHOR]

Pixel clustering is a technique of content-adaptive data embedding in the area of high-performance reversible data hiding (RDH). Using pixel clustering, the pixels in a cover image can be classified into different groups based on a single factor, which is usually the local complexity. Since finer pixel clustering seems to improve the embedding performance, in this manuscript, we propose using two factors for two-dimensional pixel clustering to develop high-performance RDH. Firstly, in addition to the local complexity, a novel factor was designed as the second factor for pixel clustering. Specifically, the proposed factor was defined using the rotation-invariant code derived from pixel relationships in the four-neighborhood. Then, pixels were allocated to the two-dimensional clusters based on the two clustering factors, and cluster-based pixel prediction was realized. As a result, two-dimensional prediction-error histograms (2D-PEHs) were constructed, and performance optimization was based on the selection of expansion bins from the 2D-PEHs. Next, an algorithm for fast expansion-bin selection was introduced to reduce the time complexity. Lastly, data embedding was realized using the technique of prediction-error expansion according to the optimally selected expansion bins. Extensive experiments show that the embedding performance was significantly enhanced, particularly in terms of improved image quality and reduced time complexity, and embedding capacity also moderately improved. [ABSTRACT FROM AUTHOR]

Reversible Data Hiding in Encrypted Image (RDHEI) is a technology for embedding secret information in an encrypted image. It allows the extraction of secret information and lossless decryption and the reconstruction of the original image. This paper proposes an RDHEI technique based on Shamir's Secret Sharing technique and multi-project construction technique. Our approach is to let the image owner hide the pixel values in the coefficients of the polynomial by grouping the pixels and constructing a polynomial. Then, we substitute the secret key into the polynomial through Shamir's Secret Sharing technology. It enables the Galois Field calculation to generate the shared pixels. Finally, we divide the shared pixels into 8 bits and allocate them to the pixels of the shared image. Thus, the embedded space is vacated, and the generated shared image is hidden in the secret message. The experimental results demonstrate that our approach has a multi-hider mechanism and each shared image has a fixed embedding rate, which does not decrease as more images are shared. Additionally, the embedding rate is improved compared with the previous approach. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Chongqing University of Posts & Telecommunications (Natural Science Edition) is the property of Chongqing University of Posts & Telecommunications and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper proposes a multi-hider dual-image reversible data-hiding algorithm. Generating dual stego images, the proposed algorithm provides a high embedding capacity, exhibits high image quality, offers reversibility to restore the stego images, and suggests seven levels of secret message extraction. The message embedding in our algorithm contains two phases. In Phase-1, we embed an n-ary secret message vector followed by an m-ary secret message in each pixel using two distinct secret keys when rendering a new image from the source and target images using an optimal weighted color-transfer process. This phase produces a tentative stego image which exhibits a new color appearance, different from the input source image. In Phase-2, we introduce a weighted modulus operation to embed a k-ary secret message vector into a dual-pixel constructed from the tentative stego image. The message concealment is elaborately designed so that the hidden secret messages are intact. This phase produces dual stego images which carry three distinct secret messages. Using legitimate secret keys, an authorized receiver can extract one or parts of secret messages and recover the tentative stego color-transferred image without arousing any suspicion. The experimental results and analysis confirm that our scheme can resist RS and PVD steganalytic attacks. In addition, our algorithm provides both high embedding capacity and better image quality, outperforming its counterparts. To the best of our knowledge, our scheme is the first in the relevant literature that provides multi-hider reversible data hiding, thereby offering various levels of message extraction for secure data communication. [ABSTRACT FROM AUTHOR]

Pixel prediction is an important issue in the field of reversible data hiding. Neural networks are gradually used to improve the accuracy of pixel prediction owing to their excellent performance. However, current neural network-based pixel predictors are designed for natural images and do not consider the characteristics of medical images. Therefore, in this paper, we propose a dual-branch neural network-based reversible data hiding scheme for medical images. Detailedly, considering the characteristics of medical images, in which complex and smooth regions are more clearly distinguished, we present a clustering method to classify pixels into three classes according to their complexities, and generate masks to assist pixel prediction. Then, in the prediction stage, a dual-branch neural network-based pixel predictor is designed to extract unique and shared features, and a convolutional block attention module is used to optimize the extracted features. Finally, in the embedding stage, considering the characteristics of region of interest (ROI) and region of non-interest (NROI) in medical images, we design a class-based embedding algorithm, which can prioritize embedding data into NROI with low complexity and then sequentially into low texture complexity region and high texture complexity region of ROI. Experimental results show that our scheme can achieve better performance of pixel prediction and data embedding than existing state-of-the-art works. • A novel neural network-based PEE-RDH scheme for medical images is proposed. • We design an efficient neural network-based pixel predictor to obtain sharper PEH. • A class-based embedding strategy is exploited to reduce ROI distortion. • Unique features of different classes of pixels are considered in feature extraction. • Our scheme achieves better prediction accuracy and embedding performance. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) technology is an effective means to ensure the secrecy of information transmission. In particular, the interpolation-based RDH algorithm is widely used due to its advantages of large embedding capacity, good visualization, and low computational cost. However, existing interpolation-based RDH algorithms have a common problem that the algorithm performance is greatly affected by the interpolation accuracy and image texture. This paper proposed a novel difference division interpolation (DDI) method that exploits the difference between the original pixels and predicted pixels to construct the cover image (CI) so that the pixel error is within a fixed range and independent of the image texture. Meanwhile, to avoid information aggregation, an adaptive chunking strategy (ACS) is designed to replace the traditional fixed chunking mode. The chunking mode and the number of embeddable bits for every non-reference pixel can be adaptively selected according to the embedding capacity, which enhances the visual quality of images. In addition, an out-of-bounds adjustment (OA) method is introduced to minimize the distortion of the steganographic image (SI) and solve the pixel underflow and overflow. Compared with existing algorithms, experimental results show the superiority of the proposed scheme. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) schemes based on pixel value ordering have gained significant popularity due to their unique capability of providing high-quality marked images with a decent embedding capacity, while also enabling secret information extraction and the lossless recovery of the original images at the receiving side. However, the marked image quality may be distorted severely when the pixel value ordering (PVO) method is employed in a layer-wise manner to increase the embedding capacity. In this paper, a new high-capacity RDH scheme using a complementary strategy is introduced to overcome the limitation of the image quality in the case of layer-wise embedding. The proposed RDH scheme first divides the cover image into non-overlapping blocks of 2 × 2 pixels uniformly and then sorts the pixels of each block according to their intensity values. The secret data are then embedded into two layers. In the first layer, the minimum value of the block is decreased and the maximum value is increased by either 1 or 2 to embed the secret data bits. The second layer is used as a complement to the first layer and is in symmetry with the first layer. In the second layer, the proposed RDH scheme increases the minimum valued pixel and decreases the maximum valued pixel in order to minimize the distortion resulting from the first layer embedding and to embed an additional amount of the secret data. As a result, the proposed RDH scheme significantly increases the embedding capacity, which is clearly evident from the conducted experimental results. [ABSTRACT FROM AUTHOR]

Reversible data hiding is an algorithm that has ability to extract the secret data and to restore the marked image to its original version after data extracting. However, some previous schemes offered the low image quality of marked images. To solve this shortcoming, a new reversible data hiding scheme based on pixel value ordering and edge detection mechanism is proposed. In our proposed scheme, the edge image is constructed to divide all pixels into the smooth regions and rough regions. Then, the pixels in the smooth regions are separated into non overlapping blocks. Then, by taking advantages of the high correlation of current pixels and their adjacent pixels in the smooth regions, PVO algorithm is applied for embedding secret data to maintain the minimum distortion. The experimental results showed that our proposed scheme obtained the larger embedding capacity. Moreover, the greater image quality of marked images are achieved by the proposed scheme than that other previous schemes while the high EC is embedded. [ABSTRACT FROM AUTHOR]

As a specific data hiding technique, reversible data hiding (RDH) has recently received extensive attention. By this technique, both the embedded data and the original cover image can be exactly extracted from the marked image. In our previous work, a general expansion-shifting model for RDH is proposed by introducing the so-called reversible embedding function (REF). With REF, RDH can be designed and the corresponding rate-distortion formulations can be established, providing an approach to optimize the reversible embedding performance. In this paper, by extending our previous work, optimal REF for one-dimensional histogram is investigated, and all optimal REF are derived in this case when the maximum modification to the cover pixel is limited as a small value. Moreover, based on the derived optimal REF for one-dimensional histogram and multiple histograms modification, a practical RDH scheme is presented and it is experimental verified better than some state-of-the-art algorithms in terms of capacity-distortion performance. [ABSTRACT FROM AUTHOR]

While the existing reserving room before encryption (RRBE) based reversible data hiding in encrypted image (RDHEI) schemes can achieve decent embedding capacity, the capacity of the existing vacating room by encryption (VRBE) based schemes is relatively low. To address this issue, this paper proposes a generalized framework for high-capacity RDHEI for both the RRBE and VRBE cases. First, an efficient embedding room generation algorithm (ERGA) is designed to produce large embedding room using pixel prediction and entropy encoding. Then, we propose two RDHEI schemes, one for RRBE, another for VRBE. In the RRBE scenario, the image owner generates the embedding room with ERGA and encrypts the preprocessed image using stream cipher with two encryption keys. Then, the data hider locates the embedding room and embeds the additional encrypted data. In the VRBE scenario, the cover image is encrypted by an improved block modulation and permutation encryption algorithm, where the spatial redundancy in the plain-text image is greatly preserved. Then, the data hider applies ERGA on the encrypted image to generate the embedding room and conducts data embedding. For both schemes, receivers with different authentication keys can conduct either error-free data extraction or error-free image recovery. The experimental results show that the two proposed schemes outperform many state-of-the-art RDHEI schemes. Besides, they can ensure high security level, where the original image can be hardly discovered from the encrypted version before or after data hiding by unauthorized users. [ABSTRACT FROM AUTHOR]

In the field of reversible data hiding in encrypted images (RDH-EI), predict an image effectively and embed a message into the image with lower distortion are two crucial aspects. However, due to the linear regression prediction being sensitive to outliers, it is a challenge to improve the accuracy of predictions. To address this problem, this paper proposes an RDH-EI scheme based on adaptive prediction-error label map. In the prediction stage, an adaptive threshold estimation algorithm based on local complexity is proposed. Then, the pixels selection method based on gradient of image is designed to train the parameters of the prediction model. In the embedding stage, reserve enough space to embed auxiliary information and secret data embedding by flipping the least significant bits (LSBs) to encrypt the original image. In the receiver, based on the prediction- error map, error-free image recovery can be achieved. Extensive experimental results have shown that the proposed method can achieve effective pixel prediction results and get a higher embedding rate (ER). [ABSTRACT FROM AUTHOR]

Reversible image data hiding technology can not only ensure that the receiver can extract the hidden data like the traditional data hiding technology, but also restore all the pixel values of the original image. Among the existing reversible image data hiding technologies, the method based on differential expansion is the most popular one. In the classical differential expansion method, a bit of data is hidden in the expanded difference of a pair of pixel values. However, expanding difference of different pixel pairs may have different effects on the fidelity of the host image, and some may cause pixel value overflow. In order to solve this problem, this paper proposes a scalable difference expansion based data hiding technology under the condition of meeting data hiding capacity. We use super pixel, more precisely pixel block, to replace a single pixel used in the traditional difference expansion as the basic carrier. Data is hidden in the expanded difference of a pair of super pixels. Adjusting the size of super pixels and/or the differential magnification can scale data hiding capacity and fidelity of stego image. Experimental results verify the feasibility of the method and our expected performance. Because the size and shape of super pixels can be adjusted, it can provide security for data hiding to some extent. In addition, the proposed algorithm does not involve complex operations such as frequency domain transform and inverse transform, so it can be applied to real-time reversible data hiding. [ABSTRACT FROM AUTHOR]

• A novel pixel-level mask autoencoder (PLMAE) is proposed to build a high-performance image recovery mechanism. • The idea of channel coding is used in the data embedding mechanism to take full advantage of PLMAE. • Compared to state-of-the-art methods, the proposed method significantly improves the embedding rate. In the study of vacating-room-after-encryption reversible data hiding in encrypted images (VRAE RDHEI), pixel prediction is an important mechanism to achieve reversibility, which has a crucial impact on the capacity and fidelity. In this paper, we propose a novel pixel-level masked autoencoders (PLMAE) as a high-performance pixel predictor for RDHEI. Unlike the original masked autoencoders (MAE), PLMAE focuses on pixel-level reconstruction rather than semantic patch-level reconstruction. The purpose of PLMAE is to spare more carrier pixels while maintaining relatively high prediction accuracy, thereby improving the RDHEI capacity. Based on PLMAE, a novel RDHEI method is proposed. In the proposed method, the data hider encodes the secret data using a polar code and then embeds the encoded data. After the image is decrypted, the receiver considers the carrier pixels as masked pixels, predicts the original states of the carrier pixels using PLMAE to extract the secret data, and then decodes the secret data and recovers the image based on the decoding results. The experimental results demonstrate that the proposed method in this paper can achieve better performance than the existing methods. [ABSTRACT FROM AUTHOR]

Pixel value ordering (PVO) prediction has become a research hotspot in reversible data hiding community and existing achievements have proved the necessity of predicting more pixels in a block. The increase in predicted pixels is beneficial to fully exploiting the redundancy of the cover image, but a single reference pixel may lead to decreased prediction quality. Given this situation, this paper proposes to develop PVO in correlated pixels construction and introduce morphology as an important theoretical tool. Several largest pixels in a block are first selected as candidate reference pixels which are to be activated in descending order. Except for the last one, each active reference pixel is used to predict all pixels to generate a correlation matrix, on which the dilation operation is carried out to pick out connected pixels that are likely to be strongly correlated with the reference pixel. Whether to activate the next reference pixel depends on the presence of disconnected pixels. Once the last reference pixel is activated, all remaining pixels will be taken as connected pixels. After the first round of embedding ends, several smallest pixels are similarly selected as candidate reference pixels to realize the second round of embedding. Experimental results demonstrate that satisfactory superiority in fidelity is achieved, e.g., the average PSNR for the Kodak image database is 63.85 dB with an embedding capacity of 10,000 bits. [ABSTRACT FROM AUTHOR]

• Balancing security and intra-block pixel correlation by adaptive pixel modulation. • A predictor based on block correlation is proposed to improve prediction accuracy. • More efficient high bit-plane code method is proposed to enhance the embedding rate. With the rapid development of telemedicine technology, electronic medical records (EMR) are facing security issues such as illegal access, leakage and malicious tampering during the transmission of electronic patient information (EPI). In view of this, a high-capacity RDHEI based on adaptive pixel modulation and high bit-plane based redundancy matrix coding (HBP-RMC) is proposed to effectively achieve patient privacy protection by embedding private data such as electronic medical records and authentication information into encrypted medical images. Specifically, the carrier image is encrypted using designed block-level disruption and adaptive pixel-modulation to preserve pixel-correlation. This method provides the basis for high embedding rates while ensuring the overall security of the image. Next, an accurate block-level pixel prediction is proposed to make full use of the high correlation to generate considerable redundancy and in balance with high prediction accuracy. Then the proposed HBP-RMC is used to maximally convert the redundant information into the embeddable space and effectively limit the size of the auxiliary information. At the decoding end, users can realize separable image restoration and information extraction according to their own keys. The maximum ERs of our scheme on the BOWS-2 and BOSSbase datasets can reach 2.9332 bpp and 3.0249 bpp, respectively. Extensive experiments prove that our algorithm outperforms some existing state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

We propose a reversible data-hiding approach in encrypted images (RDHEI) to cope with the new security threats emerging with artificial intelligence and the Industrial Internet of Things (IIoT). This dual image-based high-capacity RDHEI technique ensures security with better embedding capacity. On the sender side, the correlations of adjacent pixels are disrupted by encryption. Hence, except for the intended receiver, no one can intercept the image. This encrypted image is used as a cover image, and pixel value ordering is applied. After that, the center folding strategy is used to form dual stego images for hiding data inside both images. Pixels with maximum and minimum values are employed for data hiding. The experimental results indicate the greater resilience and imperceptibility of the discussed technique over several current strategies. The suggested plan incorporates secret bits based on the image properties. One benefit of using the suggested technique is that the process of decrypting the image and extracting the data are independent. The recipient with just the data-hiding key may recover the concealed data without any compromise, while the receiver with only the decryption key can precisely retrieve the original image without any knowledge of the data-hiding key. This makes this scheme suitable for IIoT devices with a limited processing power for image collection. [ABSTRACT FROM AUTHOR]

In recent years, reversible data hiding (RDH) in encrypted images got much attention due to its wide applications in the areas such as cloud computing, military image transmission, medical image transmission, etc. This paper introduces a new solution for reversible data hiding in encrypted images. One of the main challenges while designing a reversible data hiding scheme in an encrypted image is the embedding rate and bit error rate during image recovery. The scheme proposed in this manuscript ensures a good embedding rate and the lossless recovery of the original image. The key idea behind the proposed technique is that the encrypted image will be partitioned into non-overlapping blocks, and the pixels in each block will be categorized into white pixels and black pixels based on a predefined pattern. The black pixels will be mapped into a new pixel value based on the two bits from the secret message that is to be embedded into the selected image block. For mapping purposes, we generate four different random permutations of all the possible gray-scale values (0 to 255). At the receiver side, corresponding to each block in the image we have to generate four different weighted mesh graphs. The image recovery and data extraction are carried out by analyzing the total edge weight of these mesh graphs. The results obtained from the experimental study are much better while comparing with a few of the well-known recently introduced reversible data hiding schemes in encrypted images. [ABSTRACT FROM AUTHOR]

This paper aims to provide a comprehensive methodology for transmitting data securely between smart city applications. Reversible data hiding technique is widely used to protect secret information. Pixel value ordering (PVO) is an effective method of reversible data hiding (RDH) that sorts the pixels of a block based on their values. The pixel-based PVO (PPVO) method changes the predictive manner in PVO and achieves a high embedding capacity. However, in PPVO, the errors between the predicted pixel and the current pixel close to zero are not utilized. We propose a novel high-capacity reversible data hiding method based on PVO and median preservation to promote hiding capacity. The median preserving strategy in each block is used to compute the predicted error and to determine the smoothness of the area. If the block is a smooth area, more predicted errors are generated and fall within the range of [− 1, 1]. A modified multiple histogram scheme is applied to hide messages using predicted error shifting. Experimental results show that the proposed method has superior hiding capacity performances than that of the previous PVO-based methods. [ABSTRACT FROM AUTHOR]

Recently, reversible data hiding (RDH) based on pixel value order (PVO) has been an important research direction in the field of information security due to its high-fidelity characteristics. However, PVO-based schemes have low embedding capacities (EC) because the pixels whose prediction-error greater than 1 or less than -1 on the histogram just shifted but not selected for embedding data. Dual-image techniques have often been used in recent years. In this paper, we use dual-image to design a new shift strategy that allows secret data to be embedded in those pixels only shifted in PVO-based schemes previously to improve the EC. The number of secret message bits for each embedding is fixed in most dual-image RDH methods, which leads to image redundancy not be fully exploited. In the proposed method, the number of embedded bits changes dynamically according to the prediction-error so that the visual quality of the stego images is better. Experimental results verify that the proposed method is superior to some other state-of-the-art PVO-based and dual-image RDH methods. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) in dual images is a technique that shares secret messages into two similar shadow images, while the secret messages and the cover image can be restored only when those two shadows are gathered simultaneously. In this paper, a novel turtle shell-based RDH hiding scheme based on the symmetric property is presented in order to increase the embedding capacity and maintain good visual quality in dual images under the guidance of position-aware. First, we classify each pixel pair into one of four types according to their locations and then determine a sunflower area centered around it in order to construct the combination of positions and the embedding table. Using the embedding table, the secret messages are concealed into a cover image by generating two shadow images. At the decoder's side, the complete restoration of the secret messages and the cover image can be accomplished by identifying the position relationship between the two stego-pixel pairs. The experimental results confirmed that the proposed position-aware guided RDH scheme is superior to some of the relevant works on the aspects of embedding capacity or image quality. In addition, the proposed scheme provides a secure communication that can effectively resist attacks on the pixel value difference histogram, relative entropy, and regular singular analysis. [ABSTRACT FROM AUTHOR]

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The rapid development of image encryption and reversible data hiding technology provides protection of image copyright and privacy. For flexible management of encrypted images, there is a great deal of attention given to embedding information on encrypted images. In this paper, we propose a new technology that combines image encryption and data hiding. In the image encryption section, we propose an encryption technology that preserves the difference between pixels so that reversible data hiding can be effectively used in encrypted images. In addition, we cleverly designed the encryption so that overflow issues when embedding information does not occur in encrypted images. In the embedding information section, we adopt the histogram shifting method to conceal the secret message. We propose a technology that combines encryption and data hiding; encryption and data hiding can be completely independent, and images can be fully restored. Experimental results show that our approach is highly flexible and has a higher amount of embedding compared to those of other related works. [ABSTRACT FROM AUTHOR]

In this paper, a novel separable reversible data hiding in homomorphic encrypted images (RDHEI) using POB number system is proposed. The frame of the proposed RDHEI includes three parties: content owner, data hider, and receiver. The content owner divides original image contents into a series of non-overlapping equal-size 2 × 2 blocks, and encrypts all pixels in each block with the same key. The encryption process is carried out in an additive homomorphism manner. The data hider divides the encrypted images into the same size blocks as the encryption phase, and further categories all of the obtained blocks into two sets according to the corresponding block entropy. The embedding processes of the two sets are performed through utilizing permutation ordered binary (POB) number system. For the set with smaller entropies, all pixels in addition to the first pixel in each block are compressed by the POB number system; for the set with larger entropies, only u LSBs of all pixels are compressed in order to vacate room for embedding. The receiver can conduct image decryption, data extraction, and image reconstruction in a separable manner. Experimental results verify the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) is a technology that embeds secret data into a carrier where both the secret data and the carrier can be recovered without any data loss. Inspired by dual images technology, this article proposes to employ a high capacity RDH scheme that is based on turtle shell (TS). We start by constructing a newly designed TS-based reference matrix. Then, two meaningful shadows will be generated after hiding the secret data in the cover image with the reference matrix's help. Meanwhile, the location conflict problem is solved. On the decoder side, when both shadows are gathered, the data extraction and image recovery can be accomplished using the orientation relationship between two stego pixels that are located at the same coordinates in the two shadows and the reference matrix. Moreover, we introduce a security enhancement technology that improves the security of data extraction. The experiment shows that compared with other state-of-the-art RDH schemes, a higher embedding capacity is achieved by this method, and a good visual quality is retained. Simultaneously, the proposed scheme is effective against attacks on pixel value difference histograms (PDH) and regular singular (RS) analysis. [ABSTRACT FROM AUTHOR]

In many reversible data hiding (RDH) methods for halftone images, the traditional embedding process embeds a 1-bit secret message into each embeddable pixel or pattern. To improve the embedding efficiency and payload, we propose an RDH method used in halftone images based on the dynamic embedding states group (DESG), which can embed at least 1 bit of secret messages per embeddable pixel or pattern. First, by exploiting the statistical features of $4 \times 4$ patterns and the state sequences in each image, the DESG is constructed dynamically, including $n$ embedding states with their state patterns and state sequences. Then, secret messages are encoded by matching the longest common subsequence according to the DESG, which are split into several state sequences. The state sequences are embedded by Markov transitions between these $n$ changing state patterns. Finally, reversibility is achieved by recording the DESG as the overhead information in RDH. Experiments show that the construction of DESG can improve the embedding efficiency under the same number of embeddable pixels or patterns, and the visual distortion is also significantly reduced by flipping fewer pixels. [ABSTRACT FROM AUTHOR]

This paper proposes a novel reversible data hiding (RDH) scheme in encrypted domain for medical DICOM images. Although a lot of RDH schemes for encrypted images have been presented, however, most of them are unsuitable for medical DICOM images, as they do not utilize the features of the DICOM image format, and the recovery accuracy is low because medical images have large areas with the same pixel values. To avoid these weaknesses, our scheme segments the image and only embeds data into part of the encrypted image. The redundancy of pixel cells in DICOM images is exploited so that auxiliary data can be embedded into the image. The order of data extraction and image recovery, which can be optimized by the number of recovered blocks around the unrecovered block, is calculated to improve the recovery accuracy. In addition, to ensure the integrity of the DICOM image, the hash value of the minimum bounding rectangle of ROI and the feature bit matrix of the rest are calculated. If the image is tampered, the tampered area, especially ROI, can be accurately detected and located on the receiver side. Experimental results demonstrate the effectiveness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, we propose a reversible data hiding scheme using (5, 3) Hamming code. A cover image is partitioned into blocks of five pixels. An adjusted (5, 3) Hamming code method is then applied to find a possible modification position in these blocks to conceal message bits. The estimated position is used to determine the started pixel in the next block and this pixel may belong to the current block of pixels. This means that the overlapped pixel blocks are employed in the proposed scheme to hide secret data. As a result, the proposed scheme provides an average embedding payload reaches to 1.2 bits per pixel (bpp). The embedding positions are also utilized as a secret key to protect the hidden message from extracting attacks and extra information in the image recovering process. An original image can be recovered with no error after an extraction process has been completed. The experiment results obtained from 10,000 natural images in BOWS-2 prove that the proposed scheme can achieve a higher embedding rate, better stego-image perceptual quality, and higher security against detection and extraction attacks compared with the existing approaches. [ABSTRACT FROM AUTHOR]

Improved pixel value ordering utilizes two embedding procedures. These are the maximum and minimum embedding procedures. The maximum embedding procedure modifies a pixel by either 0 or 1, while the minimum embedding procedure modifies a pixel by either 0 or − 1. Our counter-embedding strategy modifies a corner pixel using both embedding procedures. This strategy exploits the opposing distortions of each embedding procedure and can embed up to 2 secret bits into a single pixel. The proposed scheme consists of two stages. The first stage applies the counter-embedding strategy to two corner pixels of an input block. Thus, it can conceal up to four bits per block. However, this stage generates some auxiliary information which is embedded in the second stage using the traditional IPVO. The second stage minimizes distortions by only modifying pixels that the first stage ignored. Our experimental results confirm that the proposed scheme improves the visual quality of the recent related works. On average, for embedding capacities of 10,000, 20,000, 30,000, and 40,000 bits, it increases the visual quality by at least 1.2 dB. [ABSTRACT FROM AUTHOR]

In the context of Reversible Data Hiding scheme (RDH), twin image-based methods have been widely used in recent years. Pixels of any cover image block are organized in ascending order and then modify the largest and smallest pixel to embed hidden information exploiting Pixel Value Ordering (PVO) techniques. The DPVO (Directional PVO) has been utilized in three orientations such as a horizontal, vertical and crosswise line applied one after other. Meanwhile, center folding method compresses the valuable hidden information and then embedded it within pixels of dual stego-images through averaging. The proposed scheme embed more than two data bits positions in any row of the image block which is possible by introducing a new parameter α, which was not reported by other PVO based RDH schemes. The Embedding Capacity (EC) is improved without compromising visual quality when the secret information is embedded using the center folding strategy combining with the DPVO scheme. The proposed method uses different image block sizes to demonstrate the relationship between the data hiding rate with visual quality of the stego image. The experimental outcomes indicate that the suggested method is suitable to embed high amount of hidden data with a good visual quality, that can be assured by comparing with other state-of-the-art methods. The intended result highlighted some impressive sublime features in the field of image identification, manipulation and forgery detection in which technical life stunts. This system profits enormously from numerous aspects of government and the private sector including education, economic protection, defence, intellectual property rights. [ABSTRACT FROM AUTHOR]

This paper presents a histogram based reversible data hiding (RDH) scheme, which divides image pixels into different cell frequency bands to sort them for data embedding. Data hiding is more efficient in lower cell frequency bands because it provides prediction that is more accurate. Using pixel existence probability for some pixels of ultra-low cell frequency band, another sorting is performed. Employing these two novel sorting methods, we determine smooth areas of an image more efficient than other schemes. The smoother area of the image is selected for data embedding, the less distortion of the marked image may be achieved. In another proposal, we introduce hiding intensity analysis to determine optimum prediction error to embed data. In comparison with methods that sequentially choose prediction error, this analysis results in better quality of the marked image. In effect, the proposed scheme increases the hiding capacity for a specific level of the distortion comparing to existent RDH algorithms. Experimental results confirm that the proposed algorithm outperforms state of the art ones. [ABSTRACT FROM AUTHOR]

Data hiding is a noteworthy research topic in digital technology for years. Reversible data hiding (RDH) technique plays a vital role for confirming security of the digital transmissions. A new 2-layer secure, high capacity reversible data hiding technique has been proposed, using the concept of interpolation based data hiding and difference expansion method. Unlike, state-of-the art interpolation based RDH techniques, the security has been enhanced in the proposed technique by concealing the data into the image pixels in non-sequential manner. This technique offers high-capacity data hiding, by considering the maximum difference between neighboring pixels without compromising on quality of the images. It can embed up to 3.19 bpp in Baboon image which is better than the other existing state-of-the art interpolation based RDH (IRDH) techniques. The proposed technique is sustainable against the series of tests provided by standard StirMark Benchmark 4.0 analysis. It withstands the steganalysis attacks, viz., StegExpose as a measure of security. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted images (RDH-EI) technology is widely used in cloud storage for image privacy protection. In order to improve the embedding capacity of the RDH-EI algorithm and the security of the encrypted images, we proposed a reversible data hiding algorithm for encrypted images based on prediction and adaptive classification scrambling. First, the prediction error image is obtained by a novel prediction method before encryption. Then, the image pixel values are divided into two categories by the threshold range, which is selected adaptively according to the image content. Multiple high-significant bits of pixels within the threshold range are used for embedding data and pixel values outside the threshold range remain unchanged. The optimal threshold selected adaptively ensures the maximum embedding capacity of the algorithm. Moreover, the security of encrypted images can be improved by the combination of XOR encryption and classification scrambling encryption since the embedded data is independent of the pixel position. Experiment results demonstrate that the proposed method has higher embedding capacity compared with the current state-ofthe- art methods for images with different texture complexity. [ABSTRACT FROM AUTHOR]

Data hiding in the compression domain is a very common method. Nowadays, the images to be transferred are usually compressed first. Therefore, data hiding in the compression domain becomes more and more important. Joint-neighbor coding uses the pixel that wants to be compressed, and its nearby pixels are used to embed the secret information. Absolute Moment Block Truncation Coding (AMBTC) and the joint-neighbor coding are combined to embed the secret information in the compression domain. Compared with Block Truncation Coding (BTC), AMBTC has lower computation and less distortion. The experiment result shows that our proposed method is effective. [ABSTRACT FROM AUTHOR]

Technological development leads to raising the number of digital image manipulation, especially in data security. One of the popular methods that can be used to maintain privacy is steganography. It is a technique used to hide secret messages into media such a text, image, audio, or video. Among the methods in steganography, Difference Expansion (DE), Reduced Difference Expansion (RDE), and Generalized Difference Expansion (GDE) are favored to implement. There are two main obstacles when applying this method; the first is the similarity between stego and the cover media; the second is the data capacity that can be accommodated by the cover media. Therefore, further development of these methods is needed. This research proposes applying pixel clusters based on General Difference Expansion Cluster (GDEC) to maintain the stego image quality and increase the embedding capacity. In terms of these evaluated parameters, the experiment results have proved that the proposed method can increase the average quality of each image by more than 4 dB and produces 4.00 bits per pixel (bpp). [ABSTRACT FROM AUTHOR]

Digital image steganography algorithms usually suffer from a lossy restoration of the cover content after extraction of a secret message. When a cover object and confidential information are both utilised, the reversible property of the cover is inevitable. With this objective, several reversible data hiding (RDH) algorithms are available in the literature. Conversely, because both are diametrically related parameters, existing RDH algorithms focus on either a good embedding capacity (EC) or better stego-image quality. In this paper, a pixel expansion reversible data hiding (PE-RDH) method with a high EC and good stego-image quality are proposed. The proposed PE-RDH method was based on three typical RDH schemes, namely difference expansion, histogram shifting, and pixel value ordering. The PE-RDH method has an average EC of 0.75 bpp, with an average peak signal-to-noise ratio (PSNR) of 30.89 dB. It offers 100% recovery of the original image and confidential hidden messages. To protect secret as well as cover the proposed PE-RDH is also implemented on the encrypted image by using homomorphic encryption. The strength of the proposed method on the encrypted image was verified based on a comparison with several existing methods, and the approach achieved better results than these methods in terms of its EC, location map size and imperceptibility of directly decrypted images. [ABSTRACT FROM AUTHOR]

Improved Pixel-Value-Ordering (I-PVO) based reversible data hiding scheme provides high-fidelity watermarked images with high data embedding capacity. In this paper, a new reversible data hiding scheme based on the I-PVO method is proposed to increase the data embedding capacity. The proposed scheme first divides the cover image into non-overlapping blocks of size 2 × 2 pixels uniformly, and then increases and decreases the values of highest and lowest pixels by one respectively. The proposed modification rules are used to reserve two bins which are used to increase the data hiding capacity. The pixels are sorted in ascending order to calculate two differences in the block. The difference values are calculated by considering pixel values along with their locations in the original block and are utilized to embed secret data in the highest and lowest pixel values using the proposed modification rules. While embedding the secret data, the pixel values are either increased/decreased or left unchanged according to the embedding bits. Thus, the proposed scheme embeds three bits per block in the cover image instead of two bits in the case of I-PVO on average. The experimental results show that the proposed scheme provides significantly higher data hiding capacity than the previous works. [ABSTRACT FROM AUTHOR]

In this article, a new reversible data hiding scheme using pixel-value differencing in dual images is proposed. The proposed pixel-value differencing method can embed more secret data as the difference value of adjacent pixels is increased. In the proposed scheme, the cover image is divided into non-overlapping blocks and the maximum difference value is calculated to hide secret bits. On the sender side, the length of embeddable secret data is calculated by using the maximum difference value and the log function, and the decimal secret data are embedded into the two stego-images after applying the ceil function and floor function. On the receiver side, the secret data extraction and the cover image restoration can be performed by using the correlation between two stego-images. After recovering the cover image from two stego-images, the secret data can be extracted using the maximum difference value and the log function. The experimental results show that the proposed scheme has a higher embedding capacity and the proposed scheme differs in embedding the secret data depending on the characteristics of the cover image with less distortion. Also, the proposed scheme maintains the degree of image distortion that cannot be perceived by the human visual system. [ABSTRACT FROM AUTHOR]