Reversible Data Hiding Scheme Research Articles

An Effective Multiple-Bit Data Abstraction and Lossless Retrieval without Shifting

Cryptography and Steganography are two major forms of enforcing data privacy, with the former being prevalent. For small payloads, Steganography is preferred, as the data remains concealed and abstracted. The process involves embedding bits onto a carrier image. However, the disadvantage of steganography is that the carrier image gets distorted, which is a major concern when it comes to pixel sensitive images, such as forensic and medical images that aremission critical. Furthermore, due to modifications in the pixel values, the images get distorted, which can be irrecoverable. Hence, the technique of Reversible Data Hiding(RDH) can be used as a solution. Usually two methods are used under RDH, namely Histogram Shifting (HS) and Difference Expansion (DE). Histogram Shifting method shifts all pixel values between pairs of peak and zero points, which allows data to be embedded in the intermediate points. However, this method also depends on frequencies of pixel values on the image, andthe embedding capacity varies greatly on the image. In Difference Expansion Method, the difference between a pixel and its adjacent pixels is considered to embed a single bit intoone of the pixels. Here, a scheme to embed multiple bits in a pixel is proposed, which greatly enhances the embedding capacity. Initially, three horizontally adjacent pixels are takenand the difference between the rightmost and leftmost pixel iscalculated. This difference is used to classify the centre pixel as embeddable or non-embeddable. If the pixel is embeddable, anew pixel value is calculated, which comprises of the secret bits, offset bits and flag bits, without the use of any difference expansion or histogram shifting process. The secret bits and the original pixel value can be easily recovered from the modified value using the offset and flag bits. This scheme has higher embedding capacity, and lower complexity in terms of computations, when comparedwith other RDH schemes.

Influential Metrics Estimation and Dynamic Frequency Selection Based on Two-Dimensional Mapping for JPEG-Reversible Data Hiding.

JPEG Reversible Data Hiding (RDH) is a method designed to extract hidden data from a marked image and perfectly restore the image to its original JPEG form. However, while existing RDH methods adaptively manage the visual distortion caused by embedded data, they often neglect the concurrent increase in file size. In rectifying this oversight, we have designed a new JPEG RDH scheme that addresses all influential metrics during the embedding phase and a dynamic frequency selection strategy with recoverable frequency order after data embedding. The process initiates with a pre-processing phase of blocks and the subsequent selection of frequencies. Utilizing a two-dimensional (2D) mapping strategy, we then compute the visual distortion and file size increment (FSI) for each image block by examining non-zero alternating current (AC) coefficient pairs (NZACPs) and their corresponding run lengths. Finally, we select appropriate block groups based on the influential metrics of each block group and proceed with data embedding by 2D histogram shifting (HS). Extensive experimentation demonstrates how our method's efficiently and consistently outperformed existing techniques with a superior peak signal-to-noise Ratio (PSNR) and optimized FSI.

Progressive Histogram Modification for JPEG Reversible Data Hiding

With the development of social network, a large number of private JPEG images are stored in social cloud platform. Correspondingly, the platform embeds user ID or authentication labels to manage these privacy images, preventing them from being arbitrarily accessed or tampered by illegal persons. However, data embedding in JPEG domain inevitably produces irreversible modifications to DCT coefficients, thus resulting in obvious or even serious distortion in the host JPEG images. To address this problem, this paper proposes an efficient JPEG reversible data hiding (RDH) method by constructing progressive two-dimensional histogram mappings. We firstly design distortion function to calculate the cost of each DCT frequency band, and then sort them to build histogram mapping containing a series of coefficient pairs. Subsequently, a progressive mapping mechanism is introduced to maintain most of AC coefficients unchanged. According to the given capacity, this mechanism can adaptively generate an optimum two-dimensional histogram mapping to embed secret messages. Our scheme can achieve an effective balance among embedding capacity, visual quality of the marked image and file size expansion, while keeping high cost-performance complexity. Extensive experiments demonstrate that our method outperforms existing JPEG RDH schemes in terms of visual quality and file size increment of the marked image, and provides an efficient solution for the confidentiality and security access problem of sensitive private image in cloud environment.

PVO-Based Reversible Data Hiding Using Global Sorting and Fixed 2D Mapping Modification

Pixel-value-ordering (PVO) is one of the most popular methods in reversible data hiding (RDH). In PVO based methods, pixels are processed in a block-wise way, so that the local similarities of the images are considered but the global statistical characteristics are ignored. To better utilize the correlations of pixels, this paper proposes a global sorting strategy to combine utilizations of local and global characteristics of the images. For each pixel, its prediction value and local complexity are first calculated based on its local characteristics. Then the image pixels are sorted globally according to their prediction values to generate a single-sorted pixel sequence, in which the pixels with the equal prediction values are sorted again by referring to their local complexities. In such a way, the spatial distances of image pixels are broken so that the global statistical characteristics can be well exploited. With the proposed sorting strategy, we can obtain a more regular 2D histogram by segmenting the sorted sequence for the location-based PVO (LPVO) predictor. Owe to the regular 2D histogram, we have designed an efficient 2D mapping to achieve perfect performance for all the tested images. With the proposed RDH scheme, the PSNR of the image Lena is as high as 61.86 dB and the average PSNR of the Kodak dataset reaches 63.55 dB after embedding 10,000 bits. The superiority of the proposed method has been verified by comparing with recent state-of-the-art RDH methods.

General Pairwise Modification Framework for Reversible Data Hiding in JPEG Images

Pairwise modification is one of the most effective ways to solve the critical issues of balancing the embedding capacity, image distortion, and file expansion in JPEG reversible data hiding (RDH). To design a satisfactory scheme based on pairwise modification, existing schemes focus on improving pairing rules, two-dimensional (2D) mappings, or ordering strategies separately while neglecting the connections between them. As a result, once pairing rules are changed, the correlative 2D mapping and ordering strategies are no longer available. To address such issues, this study proposes a framework that automatically generates optimal 2D mappings and efficient ordering strategies only by carefully initializing pairing rules. To construct optimal 2D mappings, a 2D mapping mathematical model is built to form a feasible 2D mapping solution space, in which optimal solutions are found, to assign efficient mappings for pairs with high probability. To design efficient ordering strategies, all frequencies are ranked according to an embedding evaluation model to determine more suitable ACs for data embedding. To initialize better pairing rules, this study selects nonzero ACs within ±2 for interblock pairing to form a more centralized pairwise histogram. The experimental results show that the proposed scheme introduces minor file expansion and obtains better visual quality than existing JPEG RDH schemes when the payload is the same as.

Color image reversible data hiding based on multi-channel synchronized histogram

Reversible data hiding (RDH) has been generally utilized in copyright protection and content integrity authentication for multimedia. In general, many typical RDH schemes are based on grayscale images. Considering that color images are widely employed in daily life, color image based RDH should be significantly concerned. Recently, color image based RDH is rare and those schemes are mostly empirically designed, which means that embedding capacity is manually allocated between different channels (such as RGB channels). In addition, most existing algorithms only focus on designing effective prediction methods to utilize the correlation in each channel, which means that the correlation between different channels is insufficiently employed and thus the algorithm performance is limited. Therefore, in this paper, the correlation between those different channels is sufficiently considered and an adaptive capacity allocation framework is proposed instead of empirical schemes. Moreover, the construction of a new synchronous histogram associated with the above-mentioned capacity allocation algorithm is proposed to further improve its performance. Experimental results demonstrate the superiority of the proposed scheme compared with other state-of-the-art ones.

Separable and reversible data hiding scheme for medical images using modified Logistic and interpolation

The interpolation technique (IT) is a fundamental tool for image processing and is commonly utilized. Various IT-based reversible data hiding (RDH) schemes for encrypted medical images have been proposed in recent years. However, these schemes have encountered issues such as simplistic encryption, low embedding rate, or incomplete separation. A high-capacity IT-based separable RDH scheme for medical images is proposed to address these issues. First, the original Logistic map is modified by adding extra parameters to increase the complexity of the key. Additionally, an encryption method via bit reorganization and diffusion is presented to encrypt the original image. Second, an improved interpolation method based on the neighbor pixel mean is proposed to interpolate the encrypted (ciphertext) image to generate a cover (interpolated) image for embedding the data. Finally, a new data embedding method is developed using the modulo-operation congruence theorem. Experimental results showed that the modified Logistic map exhibits excellent chaotic characteristics, the metrics of the proposed encryption method are close to the theoretical values, and the proposed data hiding method acquires high embedding capacity and image quality. Furthermore, the proposed scheme is a fully reversible and separable technique that achieves superior performance in comparison to various IT-based encrypted RDH schemes.

Reversible data hiding of JPEG images based on block sorting and segmented embedding

Existing JPEG image reversible data hiding (RDH) schemes based on quantized DCT (Discrete cosine transform) modification usually use non-zero or zero AC (Alternating current) coefficients as peak points for data embedding. However, this approach tends to limit the embedding capacity or result in significant file size growth. This paper proposed an RDH scheme for JPEG images based on DCT block sorting and segmented embedding. This scheme can take into account the dual advantages of having a non-zero or zero AC coefficient as the peak point, so it has both high embedding capacity and low file growth, and good visual quality. Firstly, a new DCT block sorting method is designed, the smoothness of the block is estimated by the number of zero coefficients in the EOB (End of Block) and the fluctuation of the DC coefficient in the block, and the zero coefficients in the EOB in the block have not embedded data. Then, the sorted DCT block sequence is divided into three segments, the peak points of the front two segments are (−1, 1) and (−1, 0) respectively, and the third segment may be empty but it always remains unchanged. Finally, the dynamic allocation method is used to quickly solve the optimal segmentation point to achieve the optimal embedding performance. The experimental results show that the overall performance of this scheme is better than the existing state-of-the-art algorithms.

A new paradigm for high-capacity reversible data hiding with pixel repetition and adaptive embedding

Reversible data hiding (RDH) offers a useful attribute of retaining the visual semantics with security properties, for the effective management and protection of digital images with their metadata. This paper introduces a Reversible Data Hiding (RDH) scheme with Pixel Repetition (PR) to selectively embed additional secret data. bits utilizing the image redundancy created with PR. A generalized framework of PR is first developed and the rate–distortion criterion is extended for adaptive embedding. An input image is defined to be scaled-up by replacing each original pixel (called seed) with a block of shape s×s containing the seed, where s is the scaling factor. For better utilizing this PR-based image redundancy, we then propose an RDH scheme with two-phase embedding for s=2. The first phase of the scheme embeds 4-bit data in each 2 × 2 image block using a mapping function, which is designed to modify the repeated pixels, keeping the seed intact in each block. Being invertible, the mapping function also allows another phase of embedding in the preserved seeds using an adaptive selection of their least significant bits. Compared to the prominent PR-based and other related schemes, an impressive rate–distortion performance of the proposed scheme is recorded with a greater potential for the applications that require a high and varying embedding rate with better image quality.

Reversible data hiding for JPEG images based on block difference model and Laplacian distribution estimation

Reversible data hiding (RDH) for JPEG images has attracted extensive attentions in recent years. As far, a number of related schemes have been proposed, which enhance the embedding performance by improving the strategies such as frequency selection and block sorting to choose appropriate embedding coefficients with the histogram shifting mechanism. Nevertheless, the existing methods do not fully consider the characteristics of DCT coefficients and lack accurate measurement on the embedding distortion. To address the above problems, we propose an improved general framework of RDH for JPEG images based on the Laplacian distribution model. The block difference model is first established for the alternating current (AC) coefficients fitting. Subsequently, the scale parameter is calculated to estimate the embedding efficiency of each AC coefficient, and the coefficients with high embedding efficiency are preferentially selected for embedding. Furthermore, the proposed framework can be combined with other JPEG RDH methods based on quantized DCT coefficient modification. Experimental results demonstrate that better performance in terms of both visual quality and file size preservation can be achieved with the proposed scheme compared with the state-of-the-art RDH schemes for JPEG images.

An adaptive method for prevention of overflow in reversible data hiding schemes

In reversible data hiding (RDH) schemes for images, the overflow/underflow problem must be considered to ensure reversibility. Existing techniques to avoid this problem seem to be sensitive to the working principle of a particular RDH scheme, and their performance may be adequate only when the number of problematic pixels, i.e., pixels at risk of overflow, is small or moderate compared to the total number of pixels in the image. However, when the number of problematic pixels is significantly large, the size of the recovery information needed to restore the original image increases significantly, and the performance of the RDH implementation could be affected. This paper presents an adaptive method for generating a flag array of recovery information to avoid the overflow problem. The results show that the proposed method is suitable for images with a high rate of problematic pixels since it produces much smaller recovery information streams than existing techniques. Additionally, the proposed technique allows exploiting problematic pixels during the embedding stage, increasing the effective capacity. Furthermore, the proposed method is tested with different RDH schemes and different pixel modification amplitudes, and it can preserve the structural quality of the processed images.

A prediction error based reversible data hiding scheme in encrypted image using block marking and cover image pre-processing.

A drastic change in communication is happening with digitization. Technological advancements will escalate its pace further. The human health care systems have improved with technology, remodeling the traditional way of treatments. There has been a peak increase in the rate of telehealth and e-health care services during the coronavirus disease 2019 (COVID-19) pandemic. These implications make reversible data hiding (RDH) a hot topic in research, especially for medical image transmission. Recovering the transmitted medical image (MI) at the receiver side is challenging, as an incorrect MI can lead to the wrong diagnosis. Hence, in this paper, we propose a MSB prediction error-based RDH scheme in an encrypted image with high embedding capacity, which recovers the original image with a peak signal-to-noise ratio (PSNR) of dB and structural similarity index (SSIM) value of 1. We scan the MI from the first pixel on the top left corner using the snake scan approach in dual modes: i) performing a rightward direction scan and ii) performing a downward direction scan to identify the best optimal embedding rate for an image. Banking upon the prediction error strategy, multiple MSBs are utilized for embedding the encrypted PHR data. The experimental studies on test images project a high embedding rate with more than 3 bpp for 16-bit high-quality DICOM images and more than 1 bpp for most natural images. The outcomes are much more promising compared to other similar state-of-the-art RDH methods.

Capacity-Raising Reversible Data Hiding Using Empirical Plus–Minus One in Dual Images

Electronic records of a patient’s health history are often shared among healthcare providers, and patient data must be kept secure to maintain the privacy of patients. One way of doing this is through data hiding, and this paper demonstrates a scheme to achieve this. This paper proposes a capacity-raising reversible data-hiding scheme using an empirical rules table in dual images. The aim of this research is to avoid drawing awareness to the transmission of information by providing a steganographic technique capable of embedding high-capacity data into an image while maintaining the good quality of the image. To hide the secret message(s), a rules table containing 13 entries is presented. This rules table is extendable to a table of up to 262,133 entries (with each entry containing one distinct character) that are related to the 13 entries in terms of the rules. The rules of this table are used during the embedding and extraction procedures. In the proposed method, 512 × 512 images are divided into 1 × 2 blocks where adjacent pixels are represented using x and y for both embedding and extraction, respectively. Recovery of the cover image from the stego image is also achievable during the extraction process. Conducted experiments show that the proposed method has an average pixel-to-signal noise ratio of 52.65 dB, which is higher than that achieved with the methods discussed in this paper. Additionally, the proposed method can embed a wider range of characters (depending on the image size) as compared to the rest of the methods, hence its high embedding capacity of 4.25 bpp. The proposed method can also withstand security attacks such as RS, pixel value difference, entropy, and chi-square attacks. The proposed method is also undetectable under visual attack analyses such as the difference histogram, pixel difference histogram, and visual inspection. Based on the higher embedding capacity, pixel-to-signal noise ratio, the ability of this method to be undetected under visual attack analysis, and the ability of this method to withstand security attacks, it can be concluded that the proposed method is superior to the other methods.

A Multi-Directional Pixel-Swapping Approach (MPSA) for Entropy-Retained Reversible Data Hiding in Encrypted Images.

Reversible data hiding (RDH), a promising data-hiding technique, is widely examined in domains such as medical image transmission, satellite image transmission, crime investigation, cloud computing, etc. None of the existing RDH schemes addresses a solution from a real-time aspect. A good compromise between the information embedding rate and computational time makes the scheme suitable for real-time applications. As a solution, we propose a novel RDH scheme that recovers the original image by retaining its quality and extracting the hidden data. Here, the cover image gets encrypted using a stream cipher and is partitioned into non-overlapping blocks. Secret information is inserted into the encrypted blocks of the cover image via a controlled local pixel-swapping approach to achieve a comparatively good payload. The new scheme MPSA allows the data hider to hide two bits in every encrypted block. The existing reversible data-hiding schemes modify the encrypted image pixels leading to a compromise in image security. However, the proposed work complements the support of encrypted image security by maintaining the same entropy of the encrypted image in spite of hiding the data. Experimental results illustrate the competency of the proposed work accounting for various parameters, including embedding rate and computational time.

Enabling Large-Capacity Reversible Data Hiding Over Encrypted JPEG Bitstreams

Cloud computing offers advantages in handling the exponential growth of images but also entails privacy concerns on outsourced private images. Reversible data hiding (RDH) over encrypted images has emerged as an effective technique for securely storing and managing confidential images in the cloud. Most existing schemes only work on uncompressed images. However, almost all images are transmitted and stored in compressed formats such as JPEG. Recently, some RDH schemes over encrypted JPEG bitstreams have been developed, but these works have some disadvantages such as a small embedding capacity (particularly for low quality factors), damage to the JPEG format, and file size expansion. In this study, we propose a permutation-based embedding technique that allows the embedding of significantly more data than existing techniques. Using the proposed embedding technique, we further design a large-capacity RDH scheme over encrypted JPEG bitstreams, in which a grouping method is designed to boost the number of embeddable blocks. The designed RDH scheme allows a content owner to encrypt a JPEG bitstream before uploading it to a cloud server. The cloud server can embed additional data (e.g., copyright and identification information) into the encrypted JPEG bitstream for storage, management, or other processing purpose. A receiver can losslessly recover the original JPEG bitstream using a decryption key. Comprehensive evaluation results demonstrate that our proposed design can achieve approximately twice the average embedding capacity compared to the best prior scheme while preserving the file format without file size expansion.

An Ensemble Learning Approach for Reversible Data Hiding in Encrypted Images with Fibonacci Transform

Reversible data hiding (RDH) is an active area of research in the field of information security. In RDH, a secret can be embedded inside a cover medium. Unlike other data-hiding schemes, RDH becomes important in applications that demand recovery of the cover without any deformation, along with recovery of the hidden secret. In this paper, a new RDH scheme is proposed for performing reversible data hiding in encrypted images using a Fibonacci transform with an ensemble learning method. In the proposed scheme, the data hider encrypts the original image and performs further data hiding. During data hiding, the encrypted image is partitioned into non-overlapping blocks, with each block considered one-by-one. The selected block undergoes a series of Fibonacci transforms during data hiding. The number of Fibonacci transforms required on a selected block is determined by the integer value that the data hider wants to embed. On the receiver side, message extraction and image restoration are performed with the help of the ensemble learning method. The receiver will try to perform all possible Fibonacci transforms and decrypt the blocks. The recovered block is identified with the help of trained machine-learning models. The novelty of the scheme lies in (1) retaining the encrypted pixel intensities unaltered while hiding the data. Almost every RDH scheme described in the literature alters the encrypted pixel intensities to embed the data, which represents a security concern for the encryption algorithm; (2) Introducing an efficient means of recovery through an ensemble model framework. The majority of votes from the different trained models guarantee the correct recovery of the cover image. The proposed scheme enables reduction in the bit error rate during message extraction and contributes to ensuring the suitability of the scheme in areas such as medical image transmission and cloud computing. The results obtained from experiments undertaken show that the proposed RDH scheme was able to attain an improved payload capacity of 0.0625 bits per pixel, outperforming many related RDH schemes with complete reversibility.

Reversible data hiding in JPEG document images based on zero coefficients embedding

JPEG document images are widely used in business and identity occasions. Reversible data hiding (RDH) can ensure the authenticity and integrity of JPEG document images. Most existing JPEG RDH schemes embed data into the quantified DCT coefficients with ±1 value. However, in JPEG document images, the number of ±1 coefficients is far less than that of zero coefficients, and modifying ±1 coefficients may lead to greater visual distortions. In this paper, a high capacity RDH scheme in JPEG document images based on an advanced zero coefficients embedding strategy is proposed. Firstly, JPEG document images have obvious edges and simple textures, which provide a huge number of zero coefficients to embed data. By analyzing the mean square error, zero coefficients are the best options to maintain the visual quality. Then, by minimizing a well-constructed embedding cost, the optimal zero coefficients are selected to significantly decrease the visual distortion. Lastly, the shifting gap as the small-scale overhead information is recorded in advance, so that the DCT coefficients with a great value can be avoided modification. Experiments show that the zero coefficients embedding can significantly improve the visual quality, and the maximal embedding capacity is higher compared with state-of-the-art RDH in JPEG images.

JPEG Reversible Data Hiding Using Dynamic Distortion Optimizing With Frequency Priority Reassignment

JPEG Reversible data hiding (RDH) aims at correctly extracting hidden data and perfectly recovering the original JPEG image. By combining different frequency selection and block ordering manners, appropriate AC coefficients can be determined to achieve an efficient JPEG RDH scheme using histogram shifting (HS) mechanism. Nevertheless, existing methods only rely on rough frequency band distortion model by involving all DCT blocks, ignoring the dynamic influence of block ordering on embedding block selection. As a result, JPEG image containing hidden data may have an obvious distortion and file size expansion due to an inappropriate frequency band selection. To address the aforementioned problem, we design a new JPEG RDH scheme to optimize distortion model with frequency priority reassignment. Our method firstly orders all DCT blocks by referring to zero AC coefficients of each block. Subsequently, based on the given secret data, only partial ordered blocks are selected to calculate the distortion of each DCT frequency, which can further optimize unit distortion caused by shiftable coefficients. Furthermore, we employ the adjustment parameter to adaptively reassign the priority of each frequency band based on its influence on file size expansion, which can significantly reduce file size expansion of the marked JPEG image. Extensive experiments demonstrate that our method outperforms existing JPEG RDH methods with better visual quality and smaller file size increment of the marked image.

Reversible Data Hiding Using an Improved Pixel Value Ordering and Complementary Strategy

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.

Reversible data hiding for color images based on pixel value order of overall process channel

Color image Reversible Data Hiding (RDH) is getting more and more important since the number of its applications is steadily growing. This paper proposes an efficient color image RDH scheme based on pixel value ordering (PVO), in which the channel correlation is fully utilized to improve the embedding performance. In the proposed method, the channel correlation is used in the overall process of data embedding including prediction stage, block selection and capacity allocation. In the prediction stage, since the pixel values in the co-located blocks in different channels are monotonically consistent, the large pixel values are collected preferentially by pre-sorting the intra-block pixels. This can effectively improve the embedding capacity of RDH based on PVO. In the block selection stage, the description accuracy of block complexity value is improved by exploiting the texture similarity between the channels. The smoothing the block is then preferentially used to reduce invalid shifts. To achieve low complexity and high accuracy in capacity allocation, the proportion of the expanded prediction error to the total expanded prediction error in each channel is calculated during the capacity allocation process. The experimental results show that the proposed scheme achieves significant superiority in fidelity over a series of state-of-the-art schemes. For example, the PSNR of the Lena image reaches 62.43 dB, which is a 0.16 dB gain compared to the best results in the literature with a 20,000bits embedding capacity.