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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.

Grayscale-invariant reversible data hiding (RDH) in color images was developed recently in which the grayscales of the marked color image are required to be the same as that of the host color image. Recently, some grayscale-invariant RDH schemes were proposed but their performance on embedding capacity and distortion is not satisfactory due to the large number of correction bits generated for losslessly recovering the host green scales. In this work, we propose a grayscale-invariant RDH method which reduces the need for correction bits. We design a self-correcting mechanism which modifies the green scales for keeping grayscales unchanged while remembering the information of the host green scales. To obtain this task, we observe that all previous methods generated correction bits in a functional approach which results in many correction bits. Instead of the functional approach, we use a relational approach to preserve the grayscales. By this approach, the proposed algorithm only has to generate a small number of correction bits for recovering green scales. Moreover, this relational approach allows the algorithm to embed more message bits into some green scales. The experimental results show that the proposed method significantly improves the embedding capacity and the rate-distortion performance compared to previous works.

In this paper, a novel reversible data hiding method for encrypted images (RDHEI) is proposed. An efficient coding scheme based on cyclic binary Golay (23, 12) code is designed to embed additional data into the least significant bits (LSBs) of the encrypted image. The most significant bits (MSBs) are used to ensure the reversibility of the embedding process. The proposed scheme is lossless, and based on the receiver’s privileges, allows recovery of marked data, original data and embedded data. Furthermore, the scheme can be used with any type of data, however it is best suited to 16-bit DICOM images of monochrome photometric interpretation. A modification to the standard DICOM network model was also introduced, to point out an example application of the proposed RDHEI method, i.e. an anonymized data storage outsourcing. A computer-based analysis has been carried out and simulation results are shown at the end of this paper.

Background Medical image data, like most patient information, have a strong requirement for privacy and confidentiality. This makes transmitting medical image data, within an open network, problematic, due to the aforementioned issues, along with the dangers of data/information leakage. Possible solutions in the past have included the utilization of information-hiding and image-encryption technologies; however, these methods can cause difficulties when attempting to recover the original images. Methods In this work, we developed an algorithm for protecting medical image key regions. Coefficient of variation is first employed to identify key regions, a.k.a. image lesion areas; then additional areas are processed as blocks and texture complexity is analyzed. Next, our novel reversible data-hiding algorithm embeds lesion area contents into a high-texture area, after which an Arnold transformation is utilized to protect the original lesion information. After this, we use image basic information ciphertext and decryption parameters to generate a quick response (QR) code used in place of original key regions. Results The approach presented here allows for the storage (and sending) of medical image data within open network environments, while ensuring only authorized personnel are able to recover sensitive patient information (both image and meta-data) without information loss. Discussion Peak signal to noise ratio and the Structural Similarity Index measures show that the algorithm presented in this work can encrypt and restore original images without information loss. Moreover, by adjusting the threshold and the Mean Squared Error, we can control the overall quality of the image: the higher the threshold, the better the quality and vice versa. This allows the encryptor to control the amount of degradation as, at appropriate amounts, degradation aids in the protection of the image. Conclusions As shown in the experimental results, the proposed method allows for (a) the safe transmission and storage of medical image data, (b) the full recovery (no information loss) of sensitive regions within the medical image following encryption, and (c) meta-data about the patient and image to be stored within and recovered from the public image.

In this paper, a new reversible data hiding scheme in encrypted binary image is proposed by shared pixel prediction and halving compression. We first divide binary image into non-overlapping pure color blocks and non-pure color blocks, and then partition each non-pure color block as shared pixels and embeddable pixels by a cross-segmentation mechanism. Then, a location sequence which marked all blocks is further compressed by halving compression and is considered as auxiliary data. Subsequently, after performing image encryption, data hider embeds additional data into the pixels of pure color blocks and embeddable pixels of non-pure color blocks. Finally, separable operations of data extraction, direct image decryption, and image recovery are conducted by the receiver. With shared pixel prediction mechanism, perfect image recovery can be achieved. Extensive experiments demonstrate that compared with existing methods, our scheme can obtain a higher visual quality of decrypted images, while maintaining a larger embedding capacity.

In recent years, the reversible data hiding (RDH) based on dual stego cover is developing rapidly because of its high capacity and low distortion. For image case, however, two consecutive images of the same image will draw the attention of adversaries during transmission. In this article, we propose a high-capacity RDH scheme using dual-channel audio, by exploiting the natural dual-channel property of the stereo audio. Specifically, we first convert secret message into novenary digits, which could increase the embedding capacity. Then, the magic matrix is used to embed the secret digit into a single-channel audio to generate two single-channel stego-audio. Finally, the two single-channel stego-audio is combined as a convention dual-channel audio. Extensive experiments have demonstrated that our proposed method could significantly boost the stego quality (the SNR is improved by 16% on average), when comparing with the state-of-the-art methods.

As an effective means to content authentication and privacy protection, reversible data hiding (RDH) permits us to hide a payload such as authentication data in a media file. The resulting marked content will not introduce noticeable artifacts. In order to achieve superior payload-distortion performance, the conventional RDH algorithms often exploit the smooth content for data embedding. Since RDH allows both the embedded payload and the raw content to be perfectly reconstructed, it is required that, the altered smooth regions within the cover should be identified without error by a data receiver. Therefore, a core work in RDH is to design an efficient content-aware algorithm that can enable a data hider to take advantages of the smooth cover elements as much as possible while the detection procedure for the marked elements should be invertible to a data receiver. This has motivated the authors to present a novel patch-level selection and breadth-first prediction strategy for efficient RDH in this paper. However, different from many conventional RDH works, the proposed approach allows a data hider to preferentially and simultaneously use adjacent smooth elements as many as possible, which can benefit data embedding procedure a lot. Experiments show that our work significantly outperforms a part of advanced RDH algorithms in terms of the payload-distortion performance, which has demonstrated the superiority and applicability.

In recent years, reversible data hiding technology in encrypted images has become an important topic for researchers. In addition, separable reversible data hiding technology in encrypted images also has been developed extensively because of its better practicability. In this paper, a new scheme of separable reversible data hiding in encrypted image is proposed based on the median-edge detector prediction. First, the predicted value of each pixel is calculated by using the median-edge detector predictor, and the difference between the original pixel and the predicted pixel is recorded according to the threshold parameter, and a label map is generated. Second, the original image is encrypted. Third, the differences and the secret bits are embedded into the pixels according to certain rules. After being compressed by using Run Length Coding and Huffman Coding, the label map is spliced to the bottom of the encrypted image. Finally, the stego-image is generated. When the receiver possesses the stego-image, which are the encrypted image that contain the hidden data, the desired image can be extracted or decrypted in accordance with a different key. The experimental results showed that our proposed scheme achieved better hiding capacity than the other schemes.

In this paper, two reversible data hiding (RDH) methods for vector quantization (VQ)-compressed images are presented. In the first method, the difference-index table instead of the standard-index table is designed, and all difference indices are then classified into two groups, i.e., the to-be-mapped group and the candidate group, according to the occurrence frequencies of them. Afterwards, the mapping table between those two groups is adaptively constructed and used to serve for data embedding. Furthermore, another joint method is conducted by combining the standard-index based method and the difference-index based method, resulting in a better embedding performance. The experimental results confirm that both proposed methods, especially the joint method, are significantly superior to the most recent schemes in terms of the embedding capacity, bitrate and embedding rate.

Reversible data hiding (RDH) methods are widely used in many privacy-sensitive real-time applications for digital images. As an efficient RDH method, prediction-error histogram (PEH) shifting technique has found wide application for its high efficiency in increasing embedding capacity. Nowadays, the performance of most PEH-based methods is evaluated only by Peak Signal to Noise Ratio (PSNR) or Structural Similarity (SSIM) Index. However, more and more applications require high quality in both PSNR and SSIM. Therefore, in this paper, we propose a new RDH method to concentrate on both PSNR and SSIM performance, which involves two key techniques: 1) an SSIM-based block selection technique, 2) a PEH-based optimal expansion bins selection technique. Through block selection, the original image is divided into two parts: smooth blocks and rough blocks. We select pixels of smooth block for double embedding and leave pixels of rough block unchanged. According to the optimal expansion bins, reasonable pixels are chosen for embedding such that the embedding distortion can be reduced. With these improvements, our proposed method has higher SSIM and PSNR after embedding compared to other PEH-based methods. The experimental results demonstrate its superiority over some state-of-the-art counterpart and other conventional PEH-based works.

In Malik et al. ’s method, each pixel can be embedded with $log_{2}3$ bits by being modified at most 1. Thus, their method achieves significant hiding capacity while maintaining good visual quality. However, in their method, the first lower and the first upper quantization levels must be excluded from data embedding in order to ensure reversibility. To this end, we propose a two-layer reversible data hiding (RDH) scheme in combination with (7,4) Hamming code. In the 1st-layer embedding, each block can be embedded with 16 bits. In the 2nd-layer embedding, each already-modified block can carry 6 bits or 12 bits by taking advantage of (7,4) Hamming code that hides three bits by modifying only one bit. At most 2-bit additional information is needed to help decoders to correctly extract the original lower and upper quantization levels. By means of two-layer embedding, our method achieves higher embedding capacity while maintaining almost the same visual quality, compared with Malik et al. ’s method. Experimental results also demonstrate our effectivity.

For reversible data hiding in encrypted image (RDHEI), the most important problem is the conflict between reversibility and embedding capacity. Reversibility has been realized by existing methods, however, the embedding capacity is still too low for practical RDHEI applications. To settle this problem, an improved RDHEI method is proposed in this article by presenting a block selection mechanism. Since extraction error occurs on blocks from which the fluctuation function fails to identifies the flipped part, we propose to distinguish these exceptional blocks from extraction-correct-block (ECB) (i.e., pixel block from which the hidden data can be exactly extracted) and embed additional data into only ECBs. In this way the minimum block size can be adopted to pursue high capacity. To guarantee reversibility, a new self-embedding method is proposed to embed the auxiliary information into the cover image. Finally, a new fluctuation function is also proposed to provide more ECBs and thus further improve the embedding capacity. Experimental results show that the proposed method not only achieves significant improvement in capacity but also guarantees lossless data extraction and perfect image recovery.

Typical reversible data hiding in encrypted image (RDH-EI) methods merely embed data in the encrypted domain, ignoring the requirement of the image owner for data embedding. To address this issue, this paper proposes a novel RDH-EI method with dual data embedding based on generalized integer transformation (GIT). The image owner first vacates embedding room, and performs data embedding before image encryption. After data encryption, the remote server utilizes the vacated room to further embed additional data into the encrypted image. The embedded data by the image owner and remote server can be extracted exactly, and the original image can be recovered losslessly. The experimental results prove the effectiveness of the proposed method.

Most existing AMBTC (absolute moment block truncation coding)-based reversible data hiding (RDH) schemes cannot be decoded by traditional AMBTC decoders, because they change the coding structure of the AMBTC compressed code stream, which is unidentified for decoders. Even if some AMBTC-based RDH methods can be decoded by traditional AMBTC decoders, but the obtained payload is low. To this end, in this paper, a high-capacity and decodable AMBTC-based RDH scheme is presented. It is well observed that an $m\times n$ -sized bitmap has $2^{m\times n}$ combinations of ‘1’ and ‘0’. However, all the bitmaps of an image occupy only a small part of all the combinations, and a large part are not used in this image. Motivated by this observation, we propose a one-to-many map between the used and unused combinations, in which one used bitmap can be mapped to multiple unused combinations, achieving high payloads (e.g., $\log _{2} 25$ bits for one bitmap of Lena), and more importantly, completely reserving the coding structure of the AMBTC-compressed code. Unlike existing decodable AMBTC-based RDH methods only capable of achieving a fixed payload for one test image, our method can adjust adaptively payloads according to the required visual quality by introducing a predefined threshold. The experimental results also demonstrate that our proposed scheme can largely increase the payload on the basis of maintaining good visual quality.

Reversible data hiding (RDH) algorithm is developing rapidly for many years. Usually, the histogram shifting (HS) based RDH algorithm has two main steps: Firstly, a steep difference histogram is generated with some effective methods for difference. Secondly, by extending and shifting some differences in the histogram, bits of information can be embedded into the cover image which can be restored reversibly. In this paper, we proposed the second-order difference to obtain a steeper difference histogram. Firstly, we slide a window with size 2 × 2 through the image. For each block, we can get the two first-order differences by calculating the absolute values of the two differences for its two columns. Thus, the second-order difference of each block, which is the absolute values of the difference of the two first-order differences, can be obtained. By extending and shifting the second-order difference, a bit may be embedded into the block finally. Experiments reveal that the proposed algorithm outperforms the previous state-of-the-art RDH methods in terms of the computational complexity, image distortion and the embedding performance.

NTRU (Number Theory Research Unit) has the characteristics of resistance to quantum computing attacks, fast encryption and decryption, and high security. It is very suitable for wireless confidential data networks and authentication systems. Combined with reversible data hiding technology, a separable reversible data hiding scheme in homomorphic encrypted domain based on NTRU is proposed. The image owner directly divides the cover-image into groups of a reference pixel and T adjacent pixels. Then, the grouped image is encrypted by NTRU. Finally, the encrypted image is uploaded to the data hider. The encrypted image is divided into groups by the same grouping method as the image owner. After that, the data hider calculates T absolute differences of adjacent pixels in each group to obtain histogram of the absolute differences. The additional data can be embedded into the encrypted image by shifting histogram of the absolute differences. After receiving the encrypted image with hidden data, the receiver can either use the data hiding key to directly extract the additional data from encrypted domain to obtain the encrypted image, or use the private key and data hiding key to extract the additional data from plaintext domain to get the cover-image. Experimental results show that our scheme has higher security and better embedding performance comparing with other state-of-the-art works.

With the rise of non-volatile memory used in cloud service, it becomes urgent to reduce the write cost so as to improve the data manipulation capability. This paper proposed a high embedding efficiency reversible data hiding scheme for encrypted images (RDH-EI). It embeds data at the locations of most significant bit (MSB) using matrix encoding, resulting in a high embedding efficiency. In order to restore the image completely at the receiver side, a highly accurate MSB prediction based on orthogonal projection technique is preprocessed on the original image and the prediction result is self-embedded to help recover the image. The experimental results verify that the proposed scheme outperforms the previous related schemes, it can achieve a higher embedding capacity of 0.412 bits per pixel at average, moreover, a significantly higher embedding efficiency of 3.43 bits per change is obtained. That means the proposed scheme can reduce the write cost by minimizing the modification in the case of the same payload and is especially suitable for applications used the non-volatile memory. Meanwhile, the process of data extraction is error free and the image can be recovered completely.

Reversible data hiding (RDH) in color image is an important topic of data hiding. This paper presents an efficient RDH algorithm for color image via double-layer embedding. The key contribution is the proposed double-layer embedding technique based on histogram shifting (HS). This technique exploits image interpolation to generate prediction error matrices for HS in the first-layer embedding and uses local pixel similarity to calculate difference matrices for HS in the second-layer embedding. It inherits reversibility from HS and makes high embedding capacity due to the use of double layers in data embedding. In addition, inter-channel correlation is incorporated into the first-layer embedding and the second-layer embedding for generating histograms with high peaks, so as to improve embedding capacity. Experiments with open standard datasets are done to validate performance of the proposed RDH algorithm. Comparison results show that the proposed RDH algorithm outperforms some state-of-the-art RDH algorithms in terms of embedding capacity and visual quality.

International audience; Today, 3D objects are an increasingly popular form of media. It has become necessary to secure them during their transmission or archiving. In this paper, we propose a two tier reversible data hiding method for 3D objects in the encrypted domain. Based on the homomorphic properties of the Paillier cryptosystem, our proposed method embeds a first tier message in the encrypted domain which can be extracted in either the encrypted domain or the clear domain. Indeed, our method produces a marked 3D object which is visually very similar to the original object. It seeks to be format compliant and to preserve the original size of the data, without the need for an auxiliary file. Moreover, large keys are used, rending our method secure for real life applications.

Reversible data hiding (RDH) has become a hot spot in recent years as it allows both the secret data and the raw host to be perfectly reconstructed, which is quite desirable in sensitive applications requiring no degradation of the host. A lot of RDH algorithms have been designed by a sophisticated empirical way. It is not easy to extend them to a general case, which, to a certain extent, may have limited their wide-range applicability. Therefore, it motivates us to revisit the conventional RDH algorithms and present a general framework of RDH in this paper. The proposed framework divides the system design of RDH at the data hider side into four important parts, i.e., binary-map generation, content prediction, content selection, and data embedding, so that the data hider can easily design and implement, as well as improve, an RDH system. For each part, we introduce content-adaptive techniques that can benefit the subsequent data-embedding procedure. We also analyze the relationships between these four parts and present different perspectives. In addition, we introduce a fast histogram shifting optimization (FastHiSO) algorithm for data embedding to keep the payload-distortion performance sufficient while reducing the computational complexity. Two RDH algorithms are presented to show the efficiency and applicability of the proposed framework. It is expected that the proposed framework can benefit the design of an RDH system, and the introduced techniques can be incorporated into the design of advanced RDH algorithms.

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

K-pass pixel value ordering (PVO) is an effective reversible data hiding (RDH) technique. In k-pass PVO, the complexity measurement may lead to a weak estimation result because the unaltered pixels in a block are excluded to estimate block complexity. In addition, the prediction-error is computed without considering the location relationship of the second largest and largest pixels or the second smallest and smallest pixels. To this end, an improved RDH technique is proposed in this paper to enhance the embedding performance. The improvement mainly lies in the following two aspects. First, some pixels in a block, which are excluded from data hiding in some existing RDH methods, are exploited together with the neighborhood surrounding this block to increase the estimation accuracy of local complexity. Second, the remaining pixels in a block, i.e., three largest and three smallest pixels are involved in data embedding. Taking three largest pixels for example, when the difference between the largest and third largest pixels is relatively large (e.g., > 1), we improve k-pass PVO by considering the location relationship of the second largest and largest pixels. The advantage of doing this is that the difference valued 3 between the maximum and the second largest pixel which is shifted in k-pass PVO, is able to carry 1 bit data in our method. In other words, a larger amount of pixels are able to carry data bits in our scheme compared with k-pass PVO. Abundant experimental results reveal that the proposed method achieves preferable embedding performance compared with the previous work, especially when a larger payload is required.

Histogram shifting (HS) as a typical reversible data hiding (RDH) scheme is widely researched due to its high quality of stego-image. During HS process, the selected side information, i.e., peak and zero bins, usually greatly affects the performance of stego-image. Due to the massive solution space and burden in distortion computation, conventional HS-based schemes commonly utilize some empirical criterions associated with many artificial-designed constraints to determine side information, which could not lead to a global optimal performance for HS-based RDH. Later, our previous work proposed an adaptive information selection scheme for “multiple embedding” method by removing lots of constraints employed in conventional schemes. However, those constraints could not be completely avoided. Those chosen peak and zero bins in “multiple embedding” process are required to be different with each other, since they are commonly determined at one time as side information. In this paper, we employ “multilevel embedding” method and contrive to get rid of these above-mentioned constraints, which are called “unnecessary constraints” in this paper, so as to search essential global optimal side information around the entire solution space for HS-based RDH. Apparently, the process will dramatically increase the solution space and computation complexity. To effectively control the time cost, two novel approaches are proposed: 1) A pattern-based rapid performance evaluation method is designed to compute the rate and distortion; 2) Spirited by our previous work, a problem-oriented designed evolutionary algorithm, i.e., transfer learning-based genetic algorithm, is proposed to perform high-efficiency search around the entire huge solution space. For a given data payload, the proposed scheme could adaptively determine the optimal combination of peak and zero bins without any unnecessary constraint. The experimental results demonstrate the superiority of the proposed scheme compared with other state-of-the-art methods.

Recently, reversible image data hiding with contrast enhancement (CE) has been proposed so that a contrast-changed image can be converted to its original version when needed. Several reversible image CE methods have been proposed by adopting the technique of reversible data hiding (RDH) to embed the recovery information into the contrast-enhanced images. In these methods, the 1D histogram is calculated and then modified to achieve the effects of histogram equalization (HE). Meanwhile, the 2D histogram has been used in image CE and demonstrated remarkable advantages in improving the image quality. In this paper, the method based on the 2D histogram modification is proposed to perform image CE and RDH simultaneously. In particular, a preprocessing strategy is developed to merge the adjacent bins in 2D histogram to prevent the overflow and underflow of the pixel values due to HE. The changes made in preprocessing is minimized by choosing the lowest bins for merging, while the CE effects can be achieved by expanding the highest bins for data embedding. The experimental results on two sets of test images have clearly demonstrated the efficacy of the proposed method for reversible image CE. The evaluation results are given to show its superior performances in CE and image quality preservation by comparing with the state-of-the-art approaches.

Social networking and cloud computing are being extensively used, and in this era, the frequency of sending information or images to each other is increasing. The prevention of private information leakage during communication over the Internet has become a concern in the past decades. Several data protection methods, such as cryptographic, watermarking, and steganography techniques, have been proposed to protect private data. In this paper, an embedding method is proposed based on an absolute moment block truncation coding (AMBTC)-compressed image. High and low mean tables are extracted from a compressed image and are divided into non-overlapping blocks. An adaptive variable N-bit bit plane truncation image embedding method is proposed to embed the secret data in each block. In this method, at the receiver end, the secret data are extracted, and the original AMBTC image could be recovered by recalling the stored peak and zero points. In addition, a chaotic encryption scheme is integrated into the proposed system to improve robustness against security vulnerability. The results show that the proposed method has superior performance and higher payload compared with the reference methods.

Reversible data hiding in encrypted image (RDHEI) is a technology that can simultaneously implement privacy protection and reversible information hiding. For RDHEI, the main problem is the conflict between embedding capacity and real reversibility. In this paper, to solve such a conflict, a new block-level image encryption method is proposed to fulfill privacy protection while preserving the spatial correlation of pixels inside pixel block. On this basis, a new reversible data hiding method based on block selection is also proposed. Specifically, pixel blocks are classified into embeddable block (EB) and non-embeddable block (NEB). Then, additional data is embedded into only EBs and the position file locating EB is also embedded using a new self-embedding method. Experimental results demonstrate that the proposed method not only achieves high embedding capacity, but also guarantees lossless data extraction and perfect image recovery.

Prediction-error expansion (PEE) methods usually involve the shifting process between peak points and zero points in order to vacate room for embedding. This occurrence will inevitably impose a troublesome because overflow/underflow issue after data embedding may occur, in turn, it dramatically increases the amount of auxiliary information to be transmitted or map information to be embedded. Besides, PEE-based reversible data hiding in encrypted images (RDHEI) methods usually adopt a block-size encryption strategy, but the correlation reservation of intra-block for subsequently embedding may leave opportunities for potential attacks. To deal with these issues, we proposed a novel RDHEI method with the functionality of embedding synchronized with re-encryption, which is well carried out by a data hider using a permutation ordered binary (POB) number system. Unlike conventional PEE-based RDHEI techniques, this scheme takes advantage of two peak points for embedding, but thoroughly abandons the former idea of shifting process. Experimental results verify the superiority of the proposed method, which not only may extend the applications of PEE-based RDHEI schemes substantially, but also vastly extend POB number application scenarios in practice.

Medical data security is facing great challenges in medical applications due to the open internet and the semi-trusted cloud. For the sake of privacy protection and the security of medical images, this paper proposes a secure and high visual-quality framework for medical images. In this framework, a novel reversible data hiding (RDH) based on lesion extraction embeds privacy data into medical images for privacy protection and image quality improvement, homomorphic encryption based on chaotic map encrypts images for medical image security. The experiments have shown that the proposed framework increases the security of medical data and improves the visual quality of medical images significantly. The proposed RDH in this framework outperforms the other RDH methods with contrast enhancement and the proposed encryption scheme increases image security well.

Hiding a message in compression codes can reduce transmission costs and simultaneously make the transmission more secure. This paper presents an adaptive reversible data hiding scheme that is able to provide large embedding capacity while improving the quantity of modified images. The proposed scheme employs the quantization level difference (QLD) and interpolation technique to adaptively embed the secret information into pixels of each absolute moment block truncation coding (AMBTC)-compressed block, except for the positions of two replaced quantization levels. The values of QLD tend to be much larger in complex areas than in smooth areas. In other words, our proposed method can obtain good performance for embedding capacity and still meets the requirement for better modified image quality when the image is complex. The performance of the proposed approach was compared to previous image hiding methods. The experimental results show that our approach outperforms referenced approaches.

Video has become the most important medium for communication among people. Video has become the most important medium for communication among people. Therefore, reversible data hiding technologies for video have been developed so that information can be hidden in the video without damaging the original video in order to be used in the copyright protection and distribution field of video. This paper proposes a practical and genuine reversible data hiding method by using a multi-dimensional histogram shifting scheme on QDCT coefficients in the H.264/AVC bitstream. The proposed method defines the vacant histogram bins as a set of n-dimensional vectors and finds the optimal vector space, which gives the best performance, in a 4 &times, 4 QDCT block. In addition, the secret message is mapped to the optimal vector space, which is equivalent to embedding the information into the QDCT block. The simulation results show that the data hiding efficiency is the highest among the compared five existing methods. In addition, the image distortion and maximum payload capacity are measured quite high.

In this paper, we proposed a novel reversible data hiding method in encrypted image (RDHEI), which is based on the compression of pixel differences. In the proposed method, at the content owner&rsquo, side the image is divided into non-overlapping blocks, and a block-level image encryption scheme is used to generate the encrypted image, which partially retains spatial correlation in the blocks. Due to the spatial correlation, in each block the pixels are highly likely to be similar. Therefore, the pixel differences in all blocks are concentrated in a small range and can be compressed. By the compression of pixel differences, the data hider can vacate the room to accommodate secret data in the encrypted image without losing information. At the receiver&rsquo, s side, the receiver can obtain secret data or retrieve the original image using different keys with no error. The experimental results demonstrate that, compared with existing methods, the proposed method can achieve a higher capacity and visual quality.

Pattern substitution (PS) method (Ho et al., Comput. Stand. Interfaces 31:787–794, 2009) is a recent reversible data hiding method for binary images. It generates one pattern pair, the patterns in which are called PM and PF, and substitutes between them to embed one bit. Two types of PS have been proposed: non-overlapping PS and overlapping PS. However, Dong et al. (ETRI J. 37:990–1000, 2015) states that the overlapping PS sometimes cannot decode correctly, which is called as miscoding problem. Moreover, to the PS-based methods (Ho et al., Comput. Stand. Interfaces 31:787–794, 2009; Dong et al., ETRI J. 37:990–1000, 2015; Dong et al., Lect. Notes Comput. Sci. 6526:3516–3522, 2011), although chosen of two patterns to form the pattern pair which relates the embedding performance much, the previous methods only use a fixed pattern pair during the whole data hiding process. In order to overcome these two shortcomings, this paper proposes an adaptive overlapping PS method. Firstly, two modes of the embedding are proposed so that the miscoding problem can be solved. Secondly, one window which contains the context of current processing pixel is generated and updated when the process proceeds to the next pixel. Thus, the optimum pair of the local context for embedding can be chosen. Thirdly, in order to get a smaller location map, a three-round embedding mechanism is also proposed. With these three improvements, our method can embed larger payloads with less distortion than the previous works.

Histogram shifting (HS) has been proved to be a great success in reversible data hiding (RDH). To reduce the quality loss of marked media and the increase in file size, several two-dimensional (2D) HS schemes based on the characteristics of cover media have been proposed recently. However, our analysis shows that the embedding strategies used in these methods can be further optimized. In this paper, two new 2D HS schemes for RDH in H.264/AVC video are developed, one of which uses the DCT coefficient pairs with both values 0 and the other does not. The embedding efficiency of a DCT coefficient pair in different embedding modes is firstly calculated. Then, based on the obtained embedding efficiency along with the statistical distribution of DCT coefficient pairs, two better embedding strategies are proposed. The secret data is finally embedded into the pairs of DCT coefficients of the middle and high frequencies using our proposed strategies. The comparison experiment results demonstrate that our schemes can achieve enhanced visual quality in terms of PSNR, SSIM, and entropy in most cases, and the increase in file size is smaller.

To ensure the security of digital information, information needs to be stored and processed in the encryption domain during the cloud storage process, during which the user does not allow the cloud provider (CP) to access the image contents, and the CP must embed additional information in the image. Therefore, reversible data hiding in an encryption domain (RDHEI) has emerged. This paper presents an adaptive and separable multiary RDHEI method. First, the image is divided into two parts that consist of reference pixels and non-reference pixels. Next, we compute the prediction errors of the non-reference pixels, followed by a replacement of the original non-reference values with the computed prediction errors. Then, the entire image is encrypted with a specially designed stream cipher strategy so that the CP can embed additional information by modifying the prediction errors without knowing the original image. In addition, although our method vacates space before encryption, the CP can adaptively control the reserved space, unlike traditional RDHEI schemes which also vacate space before encryption. Because our method is separable, the embedded message can be extracted from both encryption and plaintext domains accurately. The experimental results demonstrate the efficacy of the proposed method.

In this paper, a reversible data hiding method in encrypted image (RDHEI) is proposed. Prior to image encryption, the embeddable pixels are selected from an original image according to prediction errors due to adjacent pixels with strong correlation. Then the embeddable pixels and the other pixels are both rearranged and encrypted to generate an encrypted image. Secret bits are directly embedded into the multiple MSBs (most significant bit) of the embeddable pixels in the encrypted image to generate a marked encrypted image during the encoding phase. In the decoding phase, secret bits can be extracted from the multiple MSBs of the embeddable pixels in the marked encrypted image. Moreover, the original embeddable pixels are restored losslessly by using correlation of the adjacent pixels. Thus, a reconstructed image with high visual quality can be obtained only when the encryption key is available. Since exploiting multiple MSBs of the embeddable pixels, the proposed method can obtain a very large embedding capacity. Experimental results show that the proposed method is able to achieve an average embedding rate as large as 1.7215 bpp (bits per pixel) for the BOW-2 database.

In this paper, we proposed a new technique for reversible data hiding based on efficient compressed domain with multiple bit planes. We conducted a sequence of experiments to use block division scheme to appraise the result with different parameters and amended the probability of zero point in every block of histogram. This scheme attained more embedding capacity and high-quality of stego-image. Experimental consequences prove that the proposed method effectively achieved the objective of high embedding capacity and sustaining the quality of image.