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Reversible data hiding in encrypted images (RDHEI) can be used as an effective technique to protect the image content and manage the secret data embedded in the encrypted domain, it is useful for storage and management of the image outsourced to the cloud. In this paper, a hierarchical reversible data hiding with high payload in encrypted images is proposed. The pixels in original image are divided into the multiple linear regressions (MLR) predictable and the no MLR predictable. The MLR predictable pixels are processed to generate two levels label map of pixels by adaptive adjustment of predicted data and multiple bits prediction (MBP). The no MLR predictable pixels are used to generate label map of pixels (LMP) by using simple one bit prediction technique. The additional data produced by compression of three LMPs are embedded into the encrypted images. Thanks to the high correlation between pixels in the clear domain of image, the proposed scheme obtains a high embedding rate. The obtained average payloads are 2.9885 bpp, 3.759 bpp and 3.883 bpp for UCID, BOWS-2 and BOSS dataset, respectively. Extensive experiments including comparison tests, usability tests and ablation tests on some standard test images and three datasets are conducted to testify the effectiveness and usability of the proposed RDHEI, and the experimental results demonstrate that the proposed scheme outperforms the state-of-the-art RDHEI methods in payload on most images, the comparisons of performance show that great improvements have been made in the proposed method. [ABSTRACT FROM AUTHOR]

In this paper, a novel, real-time, error-free, reversible data hiding method for encrypted images has been proposed. Based on the (7, 4) Hamming code, we designed an efficient encoding scheme to embed secret data into the least significant bits (LSBs) of the encrypted image. For reversibility, we designed a most significant bit (MSB) prediction scheme that can recover a portion of the modified MSBs after the image is decrypted. These MSBs can be modified to accommodate the additional information that is used to recover the LSBs. After embedding the data, the original image can be recovered with no error and the secret data can be extracted from both the encrypted image and the decrypted image. The experimental results proved that compared with existing methods, the proposed method can achieve higher embedding rate, better quality of the marked image and less execution time of data embedding. Therefore, the proposed method is suitable for real-time applications in the cloud. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted images (RDH-EI) integrates encryption with information hiding, enabling the embedding of additional data while ensuring full recovery of the original image, widely used in multimedia data protection and forensics. However, with the increasingly serious problem of data islands, the existing RDH-EI schemes for end-to-end communication scenarios can no longer meet the application requirements for multi-party data sharing. For solving this problem, this paper proposes an RDH-EI method based on Lasso regression predictor and dynamic secret sharing. First, Lasso regression predictor is proposed, which avoids the problem of over-fitting by regularizing the loss function. Then, to reserve more embeddable room, we map the prediction error and use arithmetic coding for compression. Next, the original image and auxiliary information are shared through dynamic secret sharing algorithm, and they can be transmitted to the corresponding data hiders respectively. According to the reserved room, each data hider allows for the discrete implantation of the secret bits into the corresponding encrypted image. The receiver can successfully extract the secret bits and recreate the cover image without distortion by gathering a specific percentage of marked images. Experimental results demonstrate that the suggested Lasso regression predictor has a greater prediction accuracy, outperforming contemporary methods for embedding rate. Additionally, it has great security and strong key sensitivity. [ABSTRACT FROM AUTHOR]

The rise of the Internet has transformed communication and information access, but it also raises serious privacy concerns, especially regarding personal image sharing. This paper presents a novel reversible and authenticable data-hiding scheme for encrypted images that utilizes interpolation techniques and substitution methods. Our encryption system achieves a lower correlation among neighboring pixels, ensuring a more uniform distribution in the encrypted image. The stego images do not reveal any information about the original cover image or secret data. The embedded authentication data provides the ability to verify the authenticity of the image and localize the tampering. Experimental results show that our scheme can securely protect an image from unauthorized access and verify its authenticity. [ABSTRACT FROM AUTHOR]

Encryption is one of the main means to protect the image contents from access to unauthorized users, however, if server or computer where the encrypted image is stored crashes, it becomes difficult to restore the original image in a short period of time, to solve this problem, a novel secret shares based on share matrix is proposed. The reported scheme first generate several shares by the help of sharing matrix, then these shares are shuffled in the block level, and lastly, different diffusion intensities by hyper-chaos according to the share features derived by MED prediction are conducted. Numerous experiments are given to show the robustness of the suggested approach. Moreover, encryption performance such as key-space, key sensitivity, histogram, correlation coefficient, differential attack, cropping attack are investigated. Furthermore, it is shown that the scheme can utilize the rules of shares generation to detect the tampered share and restored image, and one refinement processing of the restored image by different combination of restoration can get the better results for original image. [ABSTRACT FROM AUTHOR]

Ensuring the security of picture data on a network presents considerable difficulties because of the requirement for conventional embedding systems, which ultimately leads to subpar performance. It poses a risk of unauthorized data acquisition and misuse. Moreover, the previous image security-based techniques faced several challenges, including high execution times. As a result, a novel framework called Graph Convolutional-Based Twofish Security (GCbTS) was introduced to secure the images used in healthcare. The medical data are gathered from the Kaggle site and included in the proposed architecture. Preprocessing is performed on the data inserted to remove noise, and the hash 1 value is computed. Using the generated key, these separated images are put through the encryption process to encrypt what they contain. Additionally, to verify the user's identity, the encrypted data calculates the hash 2 values contrasted alongside the hash 1 value. Following completion of the verification procedure, the data are restored to their original condition and made accessible to authorized individuals by decrypting them with the collective key. Additionally, to determine the effectiveness, the calculated results of the suggested model are connected to the operational copy, which depends on picture privacy. [ABSTRACT FROM AUTHOR]

• A MSB prediction-based high-capacity reversible data hiding image encryption algorithm is put forward. • A high-capacity reversible data hiding method (CPHCRDH) is proposed to correct the prediction error. • Proposed method is significantly superior to the selected contrasted algorithm in six indicators. Along with the development of cloud computing, data privacy has become the focus of attention. However, the existing methods do not allow large amounts of information to be hidden in reversible ways. In this paper, a MSB prediction-based high-capacity reversible data hiding image encryption algorithm is put forward. Due to the local correlation between the pixels and their adjacent areas in a clear image, the value of adjacent two pixels are very close. For this reason, it seems reasonable to predict pixel values by using previously decrypted images, just as many image encoding and compression methods. However, in some cases, there are some errors. Therefore, the first step of the algorithm includes identifying all prediction errors in the original image and storing the information in a binary map of the error locations. After that, a high-capacity reversible data hiding method (CPHCRDH) is proposed to correct the prediction error. This method first conducts the prediction error correction before encryption, and preprocesses the original image according to the error location map to avoid all prediction errors, and then encrypts the pre-processed image. The clear image can be reconstructed without damage through MSP prediction. Finally, through the simulation experiment on three selected CT image test examples of the eyes, body and brain, it is shown that the proposed method is significantly superior to the selected contrasted algorithm in six indicators such as the horizontal and vertical correlation coefficients. [ABSTRACT FROM AUTHOR]

Reversible data hiding in encrypted images (RDH-EIs) has attracted increasing attention since it can protect the privacy of original images while exactly extracting the embedded data. In this paper, we propose an RDH-EI scheme with multiple data hiders. First, we introduce a cipher-feedback secret sharing (CFSS) technique using the cipher-feedback strategy of the Advanced Encryption Standard. Then, using the CFSS technique, we devise a new $(r,n)$ -threshold ($r\leq n$) RDH-EI scheme with multiple data hiders called CFSS-RDHEI. It can encrypt an original image into $n$ encrypted images with reduced size using an encryption key and sends each encrypted image to one data hider. Each data hider can independently embed secret data into the encrypted image to obtain a marked encrypted image. The embedded data can be extracted from each marked encrypted image using the data hiding key, and the original image can be completely recovered from $r$ marked encrypted images using the encryption key. Performance evaluations show that our CFSS-RDHEI scheme has a higher embedding rate and that its generated encrypted images are much smaller, while still being well protected, compared to existing secret sharing-based RDH-EI schemes. [ABSTRACT FROM AUTHOR]

With the rapid advancement of cloud computing technology, reversible data hiding algorithms in encrypted images (RDH-EI) have developed into an important field of study concentrated on safeguarding privacy in distributed cloud environments. However, existing algorithms often suffer from low embedding capacities and are inadequate for complex data access scenarios. To address these challenges, this paper proposes a novel reversible data hiding algorithm in encrypted images based on adaptive median edge detection (AMED) and ciphertext-policy attribute-based encryption (CP-ABE). This proposed algorithm enhances the conventional median edge detection (MED) by incorporating dynamic variables to improve pixel prediction accuracy. The carrier image is subsequently reconstructed using the Huffman coding technique. Encrypted image generation is then achieved by encrypting the image based on system user attributes and data access rights, with the hierarchical embedding of the group’s secret data seamlessly integrated during the encryption process using the CP-ABE scheme. Ultimately, the encrypted image is transmitted to the data hider, enabling independent embedding of the secret data and resulting in the creation of the marked encrypted image. This approach allows only the receiver to extract the authorized group’s secret data, thereby enabling fine-grained, controlled access. Test results indicate that, in contrast to current algorithms, the method introduced here considerably improves the embedding rate while preserving lossless image recovery. Specifically, the average maximum embedding rates for the (3, 4)-threshold and (6, 6)-threshold schemes reach 5.7853 bits per pixel (bpp) and 7.7781 bpp, respectively, across the BOSSbase, BOW-2, and USD databases. Furthermore, the algorithm facilitates permission-granting and joint-decryption capabilities. Additionally, this paper conducts a comprehensive examination of the algorithm’s robustness using metrics such as image correlation, information entropy, and number of pixel change rate (NPCR), confirming its high level of security. Overall, the algorithm can be applied in a multi-user and multi-level cloud service environment to realize the secure storage of carrier images and secret data. [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 in encrypted images (RDH-EI) schemes based on secret sharing have emerged as a significant area of research in privacy protection. However, existing algorithms have limitations, such as low embedding capacity and insufficient privacy protection. To address these challenges, this paper proposes an RDH-EI scheme based on adaptive median edge detection (AMED) and matrix-based secret sharing (MSS). The algorithm creatively leverages the AMED technique for precise image prediction and then integrates the (r, n)-threshold MSS scheme to partition the image into n encrypted images. Simultaneously, it embeds identifying information during segmentation to detect potential attacks during transmission. The algorithm allows multiple data hiders to embed secret data independently. Experimental results demonstrate that the proposed algorithm significantly enhances the embedding rate while preserving reversibility compared to current algorithms. The average maximum embedding rates achieved are up to 5.8142 bits per pixel (bpp) for the (3, 4)-threshold scheme and up to 7.2713 bpp for the (6, 6)-threshold scheme. With disaster-resilient features, the algorithm ensures (n − r) storage fault tolerance, enabling secure multi-party data storage. Furthermore, the design of the identifying information effectively evaluates the security of the transmission environment, making it suitable for multi-user cloud service scenarios. [ABSTRACT FROM AUTHOR]

Secret sharing is a data security technique that divides secret information into multiple parts, embeds these parts into various shares, and distributes these shares to different participants. The original secret information can be retrieved only when the number of shares gathered meets a required threshold. This paper proposes a secret sharing method that can hide data in encrypted images with reversibility and allows content owners to add an additional layer of security before uploading data to the cloud. This method enables the independent extraction of images and data, ensuring that the recovered images and extracted data can serve as validation information for each other. The proposed method not only enhances data security but also guarantees the accuracy of the extracted information. [ABSTRACT FROM AUTHOR]

When visual sensor networks (VSNs) enter daily life in society, they not only bring great convenience but also cause people to worry about privacy. Traditional image encryption uses the snowflake effect to protect the privacy, but this can compromise the usability of directly browsing images captured by nodes in VSNs. Recently, thumbnail-preserving encryption (TPE) has been proposed to balance image usability and privacy. However, the Markov chain's limited connectivity and high time cost, which result in low efficiency, may preclude its application in VSNs. Motivated by this, we propose a novel TPE scheme to protect the image collected in VSNs' privacy efficiently. We first deeply study the bijective relationship between the three-pixel group and its rank, and then propose a new number method for both, based on which we design the efficient rank mapping. Subsequently, an efficient thumbnail-preserving image encryption via three-pixel rank mapping (E-TPE) is designed, achieving NR security and enhancing the Markov chain's connectivity. The experiments demonstrate the scheme's efficiency; that is, it is currently the quickest ideal-TPE scheme with NR security, and a good balance is achieved between usability and privacy. [ABSTRACT FROM AUTHOR]

The reversible data hiding scheme in the encrypted domain is a potential solution to the concerns regarding user privacy in cloud applications. The 3D mesh model is an emerging file format and is widely used in engineering modeling, special effects, and video games. However, studies on reversible data hiding in encrypted 3D mesh models are still in the preliminary stage. In this paper, two novel techniques, multi-group partition (MGP) and closest pair prediction (CPP), are proposed to improve performance. The MGP technique adaptively classifies vertices into reference and embeddable vertices, while the CPP technique efficiently predicts embeddable vertices and generates shorter recovery information to vacate more redundancy for additional data embedding. Experimental results indicate that the proposed scheme significantly improves the embedding rate compared to state-of-the-art schemes and can be used in real-time applications. [ABSTRACT FROM AUTHOR]

Reversible data hiding over encrypted images (RDH-EI) technology is a viable solution for privacy-preserving cloud storage, as it enables the reversible embedding of additional data into images while maintaining image confidentiality. Since the data hiders, e.g., cloud servers, are willing to embed as much data as possible for storage, management, or other processing purposes, a large embedding capacity is desirable in an RDH-EI scheme. In this article, we introduce a novel bi-directional block encoding (BDBE) method, which, for the first time, encodes the distances of values in a binary sequence from both ends. This approach allows for encoding images with smaller sizes compared to traditional and state-of-the-art encoding methods. Leveraging the BDBE technique, we propose a high-capacity RDH-EI scheme. In this scheme, the content owner initially predicts the image pixels and then employs BDBE to encode the prediction errors, creating space for data embedding. The resulting encoded data are subsequently encrypted using a secure stream cipher, such as the Advanced Encryption Standard, before being transmitted to a data hider. The data hider can embed confidential information within the encrypted image for the purposes of storage, management, or other processing. Upon receiving the data, an authorized receiver can accurately recover the original image and the embedded data without any loss. Experimental results demonstrate that our RDH-EI scheme achieves a significantly larger embedding capacity compared to several state-of-the-art schemes. [ABSTRACT FROM AUTHOR]

For reversible data hiding in encrypted image (RDHEI), it is an important problem to resolve the contradiction between embedding capacity and image visual quality. However, existing schemes do not maintain a good balance between them. Accordingly, we propose a multi-level block selection embedding mechanism to solve this problem. Our scheme firstly divides original image into muliple non-overlapping blocks with identical size. The most significant bit (MSB) planes of all pixels in the block are predicted from their neighboring pixels to generate a corresponding prediction error map for each block. Subsequently, the pixels are divided into eight bit planes, and the adjacent bit planes are implemented XOR operation to vacate room. Furthermore, by simulating data embedding in each block, PSNR values of each image block are sequentially generated. After encrypting the image using stream ciphers, the optimal blocks with maximum PSNR value can be selected to embed data according to the secret data capacity. Since our proposed scheme usually selects the image block with maximum PSNR value to embed secret data, it can naturally improve the image visual quality. Extensive experiments demonstrate that our scheme is effective and efficient, and outperforms existing state-of-the art methods with better visual quality and higher security performance under the given embedding capacity. [ABSTRACT FROM AUTHOR]

With the growing demands of cloud computing and privacy protection, reversible data hiding in encrypted images (RDHEI) has been gradually developed. This paper proposes a RDHEI scheme based on reserving room before encryption (RRBE). The scheme is divided into three types of users: image owner, data hider and receiver. First, the image owner preprocesses the image using a median-prediction-based pixel value ordering algorithm (M-PVO), and then encrypts the image using the Paillier homomorphic cryptosystem, and the data hider performs two stages of data embedding on the encrypted image. According to the key held by the receiver, the data embedded in different stages can be extracted and the original image can be recovered lossless. The experimental results show that the embedding rate of the first stage is about 0.7 bpp, and the embedding rate of the second stage can reach 12 bpp. Compared with other schemes, the proposed scheme has better image quality at the same embedding rate. [ABSTRACT FROM AUTHOR]

With the rapid development of 5G network, protecting multimedia data security has attracted a lot of attentions, and Reversible Data Hiding in Encrypted Image (RDHEI) has become a research hotspot, since it has the ability of hiding information while protecting the privacy of original cover images. RDHEI remains a challenging task to improve the embedding capacity under the premise of real reversibility. In this paper, we propose a RDHEI scheme with multiple data hiders based on Additive Secret Sharing (ASS) and Adaptive Bit-Plane Prediction (ABPP). First, ASS and bit-plane separation techniques are developed to encrypt an original image. It can encrypt an original image into n encrypted image shares with an encryption key and send each encrypted image share to one data hider. Then, we propose a Several-Parts-Disposable Strategy (SPDS) which is developed to generate the encrypted secret data with multiple data hiders. SPDS makes our scheme have the ability to resist collusive analysis and cooperative attacks. Finally, each data hider can embed encrypted secret data independently using ABPP embedding strategy. Furthermore, our scheme is separable and can be applied to multiparty copyright protection. In addition, we present a Shared No Key (SNK) based on secret sharing, which costs much lower computation than the literature works proposed SNK-type schemes by using homomorphic encryption. The experimental results and theoretical analysis show that our scheme is secure, high capacity and significantly outperforms previous schemes. [ABSTRACT FROM AUTHOR]

As a booming technique in the field of information security, reversible data hiding in encrypted images has attracted great concern because secret data can be recorded in the encryption domain without knowing the related encryption key and the content of original images. In this paper, a fully reversible data hiding method with high embedding capacity is proposed based on optimal block allocation with full consideration of distinct pixel characteristics. The occurrence frequency of most significant bits in smooth blocks is used to obtain embeddable space. For fluctuant blocks, a cascaded two Huffman coding is innovatively designed to compress most significant bits of each pixel to generate more spare rooms. To enhance the security, not only the original image is encrypted based on sequences generated with the high-dimension chaotic system, but also the encrypted image containing secret data is further scrambled. Compared with some state-of-the-art methods, the experimental results and analysis demonstrate that the proposed method has larger embedding capacity using different test images and image databases. [ABSTRACT FROM AUTHOR]

With the development of digital media, its security has also been emphasized, and reversible data hiding (RDH) algorithms has been widely studied. This paper studied RDH algorithms for JPEG images, designed a method to embed secret information by frequency band selection based on discrete cosine transform (DCT) coefficients, called an improved RDH (IRDH) algorithm, and conducted experiments on the USC-SIPI image set. It was found that the designed RDH algorithm had a higher embedding capacity, with an average embedding capacity of 37 031 bits at quantization factor = 50, as well as a higher peak signal-to-noise ratio (PSNR) value and a lower file size increase (FSI) value, compared with the other methods; the dispersion degree of the data obtained by this algorithm was also low. The results demonstrate the reliability of the IRDH algorithm on JPEG images, which can be extended and applied in practice. [ABSTRACT FROM AUTHOR]

To protect the security of medical images and to improve the embedding ability of data in encrypted medical images, this paper proposes a permutation ordered binary (POB) number system-based hiding and authentication scheme for medical images, which includes three parts: image preprocessing, double hiding, and information extraction and lossless recovery. In the image preprocessing and double hiding phase, firstly, the region of significance (ROS) of the original medical image is segmented into a region of interest (ROI) and a region of non-interest (RONI). Then, the bit plane of the ROI and RONI are separated and cross-reorganization to obtain two new Share images. After the two new Share images are compressed, the images are encrypted to generate two encrypted shares. Finally, the embedding of secret data and attaching of authentication bits in each of these two encrypted shares was performed using the POB algorithm. In the information extraction and lossless recovery phase, the POBN algorithm is first used to extract the authentication bits to realize image tamper detection; then, the embedded secret message is extracted, and the original medical image is recovered. The method proposed in this research performs better in data embedding and lossless recovery, as demonstrated by experiments. [ABSTRACT FROM AUTHOR]

In tandem with the fast-growing technology, the issue of secure data transmission over the Internet has achieved increasing importance. In digital media, enclosing data in images is one of the most common methods for communicating confidential information. A novel reversible data hiding in the encrypted images scheme based on selective bin models is proposed in this paper. The scheme focuses on enhancing the embedding capacity while ensuring the security of images with the help of encryption and the proposed data hiding process. For data embedding, lossless compression is utilized and the image is classified into three bins. Then, marker bits are assigned to these bins for distinguishing between embeddable and non-embeddable regions. The proposed method shows a satisfactory embedding rate for smooth images as well as complex ones due to its selective bin approach. Also, the method is separable in nature, i.e., data extraction and image recovery can be performed independently. Furthermore, the experimental results demonstrate the strategy’s effectiveness when compared with others. [ABSTRACT FROM AUTHOR]

The drawbacks of a one-dimensional chaotic map are its straightforward structure, abrupt intervals, and ease of signal prediction. Richer performance and a more complicated structure are required for multidimensional chaotic mapping. To address the shortcomings of current chaotic systems, an n-dimensional cosine-transform-based chaotic system (nD-CTBCS) with a chaotic coupling model is suggested in this study. To create chaotic maps of any desired dimension, nD-CTBCS can take advantage of already-existing 1D chaotic maps as seed chaotic maps. Three two-dimensional chaotic maps are provided as examples to illustrate the impact. The findings of the evaluation and experiments demonstrate that the newly created chaotic maps function better, have broader chaotic intervals, and display hyperchaotic behavior. To further demonstrate the practicability of nD-CTBCS, a reversible data hiding scheme is proposed for the secure communication of medical images. The experimental results show that the proposed method has higher security than the existing methods. [ABSTRACT FROM AUTHOR]

Advances in mobile communication have enabled images to be shared more conveniently, and the consequent risk of privacy breaches has been increasingly emphasized. Previously, traditional image encryption algorithms were mostly adopted by individuals to encrypt plain images into noise-like meaningless cipher images. This type of algorithm provides security for image privacy protection but is unable to achieve usability in cloud platforms. Furthermore, existing image encryption algorithms only target the protection of lossless compression or non-compressed formats images (e.g., BMP, PNG, etc.), but neglect the encryption needs of JPEG format images. Since the latter has the benefits of less file storage and excellent visual quality, it has been widely applied in a variety of scenarios. Thus, a thumbnail preserving encryption (TPE) scheme based on Markov model (TPE-MM) for JPEG images is proposed to equilibrate security and availability. Specifically, an approximate sum-preserving encryption method (ASP-EM) in restricted range based on its features is proposed to preserve the plain thumbnail features to accomplish cipher image usability. Subsequently, an adaptive encryption method based on Markov model (AEM-MM) was proposed to improve the encryption effect of cipher images and retain the compression performance of JPEG images. Simulation experiments show that the cipher image has good visual quality, low expansion rate, and is resistant to outline attacks. [ABSTRACT FROM AUTHOR]

With the swift progression of three-dimensional (3D) modeling and multimedia technology, the unauthorized duplication and manipulation of 3D point cloud data has become more prevalent. Existing watermarking algorithms designed for 3D point cloud data lack robustness against rotation, cropping, and random point addition attacks. To address the aforementioned issues, we propose a robust watermarking algorithm based on the Mahalanobis distance (MD) and feature point extraction, including zero-watermarking algorithm based on MD and watermarking algorithm based on the Intrinsic Shape signatures (ISS) feature points. Firstly, calculate the MD of point cloud data and use it to construct feature matrix. A zero-watermark image is constructed through the XOR operation of the feature matrix and the copyright information matrix. Secondly, ISS feature points can be extracted from point cloud data, which using the X and Y coordinates of the feature points as indexes. The color information of the feature points is used as host data to embed the watermark. The scale invariance of MD and the stability of ISS feature points augment the robustness of the algorithm. Experimental results demonstrate that the scheme we propose exhibits strong robustness against geometric attacks, simplification attacks, cropping attacks, reordering, and noise attacks while ensuring point cloud data coordinates are lossless. [ABSTRACT FROM AUTHOR]

As a booming technique that allows secret data extraction and information carrier recovery without any loss, reversible data hiding in different carriers has attracted more and more concerns in the field of information security. In this paper, a separable reversible data hiding technique for encrypted 3D meshes is proposed based on self-organized blocking and most significant bit (MSB) prediction. The content-owner traverses all faces of the mesh in the ascending index order. Through self-organized blocking, adjacent vertices are concentrated in different small sets. The central vertex is considered as the reference and the others as embedded vertices in each set. Then, multiple most significant bits between the central vertex and others are adaptively predicted and reserved as embeddable bits for secret data embedding. Because vertex coordinates in each set have a high space correlation and most vertices participate in the prediction process, a huge number of most significant bits can be marked as embeddable bits to embed secret data. Experimental results demonstrate that the proposed method can obtain the highest embedding rate compared with representative methods. To our best knowledge, the average embedding rate of the proposed method is about 28 bits per vertex (bpv) higher than the recently proposed method. Most importantly, instead of recovering meshes with higher quality, original meshes with high visual symmetry/quality can be recovered.

• An improved prediction method is designed to predict the current pixel value. • The multi-MSBs substitution is applied to achieve high embedding capacity. • The original image can be reconstructed losslessly by utilizing MSB prediction. Reversible data hiding in encrypted images is an effective technique to embed information in encrypted domain, without knowing the original content of the image or the encryption key. In this paper, a high-capacity reversible data hiding scheme for encrypted images based on MSB (most significant bit) prediction is proposed. Since the prediction is not always accurate, it is necessary to identify the prediction error and store this information in the location map. The stream cipher is then used to encrypt the original image directly. During the data hiding phase, up to three MSBs of each available pixel in the encrypted image are substituted by the bits of the secret message. At the receiving end, the embedded data can be extracted without any errors and the original image can be perfectly reconstructed by utilizing MSB prediction. Experimental results show that the scheme can achieve higher embedding capacity than most related methods. [ABSTRACT FROM AUTHOR]

Reversible data hiding (RDH) technique has been widely used for content authentication. However, most conventional RDH schemes generally concentrates on the rate-and-distortion performance (namely high capacity and low distortion), instead of their undetectability performance (namely security). In other words, the stego images with conventional RDH schemes could be easily detected by most steganalysis tools, e.g., SPAM, to reveal some suspicious secret data hidden in it, which increases the embedding risk. Therefore, their applications in some circumstances are restricted. In this paper, enhanced images generated by common image enhancement techniques are built as a desired carrier for RDH, to achieve both better rate-and-distortion and desired undetectability performance due to its special statistical histogram distribution, where many vacant interspaces are scattered in the histogram and suitable for histogram shifting based RDH process. In addition, considering that the enhanced images could provide much more candidate spaces for embedding, some strategies for security improvement, such as multi-feature sorting technique and so on, could be introduced. Experimental results verify the superiority of proposed scheme compared with other related algorithms. [ABSTRACT FROM AUTHOR]

Through cloud computing development, image encryption is employed to protect content-owner privacy. By the way, the need for embedding secret data in an encrypted image is the reason introducing reversible data hiding in an encrypted image. We may vacate the room before, by or after encryption to embed data. On the receiver side, data extraction can be done separately or jointly with the original image reconstruction. Meanwhile, presenting a separable scheme by vacating the room after encryption is more practical and more challenging than others which we do in this paper. In this way, we employ some notions of reversible data hiding (RDH) in a plain image, such as histogram modification and prediction-error computation. The most significant bits (MSBs) of the encrypted pixels are integrated to vacate the room for embedding data bits. The integrated MSBs would be more robust against failure of lossless reconstruction if modified for data embedding. Meanwhile, a data hider who embeds data is entirely blind to the original content. On the recipient side, data may be extracted error-freely and the original image may be reconstructed losslessly. We employ the chessboard predictor for the lossless reconstruction of the original image through prediction-error analysis. Integration of the encrypted pixels is an alternative method of compressing the encrypted pixels. Experimental results confirm that the proposed integration method outperforms the prior arts. [ABSTRACT FROM AUTHOR]

The data embedding of vacating room after encryption reversible data hiding in encrypted images (VRAE RDHEI) is performed on an encrypted image without redundancy and spatial correlation. Data extraction and image recovery rely on a range of unique mechanisms that utilize spatial correlation in the decrypted domain. Of these mechanisms, pixel prediction is among the most frequently used, directly affecting the capacity and fidelity. In this paper, we propose a novel method that uses a two-round interpolation mechanism to enhance pixel prediction precision while preserving a large number of carrier pixels. In the proposed method, the content owner uses a stream cipher to encrypt the image as a carrier. The data hider flips specific LSBs of the encrypted image for data embedding. On the receiver side, the process of data extraction and image recovery is divided into two stages. In each stage, based on the varying distributions of the original or recovered pixels with the carrier pixels, the corresponding pixel interpolation schemes are used to accurately predict the pixels for data extraction and image recovery. The results demonstrate that the proposed method can efficiently improve the capacity and fidelity with full reversibility compared to existing VRAE RDHEI methods. [ABSTRACT FROM AUTHOR]

With the rapid development of multimedia technology and the massive accumulation of user data, a huge amount of data is rapidly generated and shared over the network, while the problems of inappropriate data access and abuse persist. Reversible data hiding in encrypted images (RDHEI) is a privacy-preserving method that embeds protected data in an encrypted domain and accurately extracts the embedded data without affecting the original content. However, the amount of embedded data has been one of the major limitations in the performance and application of RDHEI. Currently, the main approaches to improve the capacity of RDHEI are either to increase the overall capacity or to reduce the length of the auxiliary information. In this paper, we propose a novel RDHEI scheme based on multi-prediction and adaptive Huffman encoding. To increase the overall capacity, we propose a multi-prediction, called MED+GAP predictor, to generate the label map data of non-reference pixels prior to image encryption. Then, an adaptive Huffman coding is designed to compress the generated labels in order to reduce the embedding length of the auxiliary information used for the extraction and recovery. Experiments show that the proposed method with MED+GAP predictor and adaptive Huffman coding improves 0.052 bpp, 0.023 bpp, and 0.047 bpp on average over the other state-of-the-art methods on the BOSSBase, BOWS-2, and UCID datasets, respectively, while maintaining security and reversibility. [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]

Information has been uploaded and downloaded through the Internet, day in and day out, ever since we immersed ourselves in the Internet. Data security has become an area demanding high attention, and one of the most efficient techniques for protecting data is data hiding. In recent studies, it has been shown that the indices of a codebook can be reordered to hide secret bits. The hiding capacity of the codeword index reordering scheme increases when the size of the codebook increases. Since the codewords in the codebook are not modified, the visual performance of compressed images is retained. We propose a novel scheme making use of the fundamental principle of the codeword index reordering technique to hide secret data in encrypted images. By observing our experimental results, we can see that the obtained embedding capacity of 197,888 is larger than other state-of-the-art schemes. Secret data can be extracted when a receiver owns a data hiding key, and the image can be recovered when a receiver owns an encryption key. [ABSTRACT FROM AUTHOR]

This paper delves into the realm of steganography, focusing on the evolution of techniques employed to conceal data within digital images. Beginning with an exploration of the motivations behind information security and the role of cryptography, the paper introduces adaptive steganography as a discreet means of incorporating private data into a cover medium. The discussion then shifts to the three key factors in image steganography - resilience, capacity, and imperceptibility - forming the foundation of effective data hiding. The spatial and frequency domain methods are compared, with specific emphasis on the classical Least Significant Bit insertion and more advanced adaptive steganography techniques. The paper further introduces edge-based steganography, highlighting the advantage of manipulating edge areas for increased imperceptibility. Moving beyond definitions and types, the paper provides a comprehensive analysis of notable research works in the field, elucidating their objectives, methodologies, results, strengths, and limitations. The conclusion reflects on the dynamic landscape of steganography, acknowledging both achievements and areas for improvement. [ABSTRACT FROM AUTHOR]

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The digital content exchange on the Internet is associated with information security risks. Hiding data in digital images is a promising direction in data protection and is an alternative to cryptographic methods. Steganography algorithms create covert communication channels and protect the confidentiality of messages embedded in cover images. Watermarking algorithms embed invisible marks in images for further image authentication and proof of the authorship. The main difficulty in the development of data hiding schemes is to achieve a balance between indicators of embedding quality, including imperceptibility, capacity, and robustness. An effective approach to solving this problem is the use of metaheuristic optimization algorithms, such as genetic algorithm, particle swarm optimization, artificial bee colony, and others. In this paper, we present an overview of data hiding techniques based on metaheuristic optimization. We review and analyze image steganography and image watermarking schemes over the past 6 years. We propose three levels of research classification: embedding purpose level, optimization purpose level, and level of metaheuristics. The results demonstrate the high relevance of using metaheuristic optimization in the development of new data hiding algorithms. Based on the results of the review, we formulate the main problems of this scientific field and suggest promising areas for further research. [ABSTRACT FROM AUTHOR]

High security and effectiveness are critical performance metrics in the data transmission process for satellite remote sensing images, medical images, and so on. Previously, the receiver could gain a high-quality cover image (lossy) after decryption in a separable manner to balance embedding capacity (EC) and security. Completely separable, reversible data hiding in encrypted image (SRDH-EI) algorithms are proposed to address this issue. In this study, the cover image was preprocessed at the sender's end. The pre-embedded pixels and most significant bits (MSB) were compressed via two coding methods to reserve space. Additionally, the header data were embedded for marking. Finally, auxiliary data and secret data were embedded in a forward "Z" and reverse "Z" shape before and after encryption, respectively. The receiver could extract secret data and decrypt the cover image separately using the keys and markers. The experimental results demonstrate that the algorithm reached a high EC for remote sensing images by utilizing pixel correlation at multiple positions within the groups. The cover image could maintain its entropy during the data embedding process, ensuring security. The decrypted image could be recovered without distortion, furthermore, the receiver could achieve complete separability, so it has good application prospects for remote sensing images. [ABSTRACT FROM AUTHOR]

Over the past few years, a considerable number of researchers have shown great interest in reversible data hiding for encrypted images (RDHEI). One popular category among various RDHEI methods is the reserving room before encryption (RRBE) approach, which leverages data redundancy in the original image before encryption to create space for data hiding and to achieve high embedding rates (ERs). This paper introduces an RRBE-based RDHEI method that employs pixel prediction, quadtree decomposition, and bit plane reordering to provide high embedding capacity and error-free reversibility. Initially, the content owner predicts the error image using a prediction method, followed by mapping it to a new error image with positive pixel values and a compressed binary label map is generated for overhead pixels. Subsequently, quadtree decomposition is applied to each bit plane of the mapped prediction error image to identify homogeneous blocks, which are then reordered to create room for data embedding. After generating the encrypted image with the encryption key, the data hider employs the data hiding key to embed the data based on the auxiliary information added to each embeddable bit plane's beginning. Finally, the receiver is able to retrieve the secret message without any error, decrypt the image, and restore it without any loss or distortion. The experimental results demonstrate that the proposed RDHEI method achieves significantly higher ERs than previous competitors, with an average ER exceeding 3.6 bpp on the BOSSbase and BOWS-2 datasets. [ABSTRACT FROM AUTHOR]

Recently, with the rapid development of cloud storage, secure cloud computing and privacy protection have attracted widespread attention. Reversible data hiding in encrypted images (RDHEI) plays an important role in it and has been paid more and more attention. In this paper, an improved RHDEI is proposed. By combining adaptive Arithmetic coding and static Huffman coding, the image bit-plane is effectively compressed and a lot of space is made for data embedding. The security of image and embedded data is guaranteed by XOR-encryption and scrambling encryption. The data extractor can embed and extract data without decrypting the carrier image to protect the privacy of the image owner. Experimental results show that the scheme can achieve an average embedding capacity (EC) of up to 3 bpp while ensuring lossless recovery of carrier images and correct extraction of embedded data. Compared with state-of-the-art RDHEI methods, our scheme achieves higher EC and better security. [ABSTRACT FROM AUTHOR]

Data hiding, also known as information hiding and digital watermarking, refers to the technology of hiding secret information in publicly available media and making it difficult for people to feel its existence. According to the survival result of the hidden information when the stego media is processed, this technology can be divided into robust, semi-fragile, and fragile watermarking. Strong robust digital watermarking is technically difficult to achieve, so it is unrealistic to apply it for digital copyright protection at present. In contrast, fragile (and semi-fragile) watermarking has good feasibility and has been used for authentication and tamper localization of the stego media. However, the existing technology has limitations. To improve the sensitivity and positioning accuracy of tampering, some algorithms embed excessive data, which greatly reduces the fidelity of stego media. To prevent third parties from bypassing integrity authentication and tamper localization, some algorithms add complex encryption algorithms to achieve the confidentiality of hidden data, which not only greatly increases the computational cost, but also destroys the blindness of data extraction. To overcome these shortcomings, this paper proposes a lightweight large-capacity image data-hiding technology. Both the data hiding and data extraction are based on looking up a shared codebook table, so the computational cost on both sides is low. The codebook table can be flexibly customized according to the agreement of the sender and receiver of the stego image. It not only ensures the fidelity of stego image but also naturally provides the confidentiality of hidden data. The experimental results and analysis show that its comprehensive performance, including imperceptibility, capacity, complexity, security, and customizability, is better than various state-of-the-art fragile watermarking techniques. Thus, the proposed technique has obvious advantages when used in image authentication, tampering localization, source tracing, and steganography. The proposed technique can be flexibly extended to hide data in other media. [ABSTRACT FROM AUTHOR]

In recent years, reversible data hiding has become one of the most commonly used techniques. In this paper, a novel dual image reversible data hiding (RDH) technique based on a quinary secret square is proposed. In this technique, the imperceptibility and data hiding capacity are improved while maintaining good image quality in a lossless manner. The information overhead sent to the receiver for extraction and recovery is also reduced. A secret square is used during the embedding and extraction processes. In addition, the use of 5-ary numbers rather than binary numbers is proposed to ensure that all secret messages are embedded from the symbols. This technique uses two pixels as a block (2 × 2) and a maximum of 25 symbols to embed the secret message. In the experiments, 25 symbols and 16 symbols were used to embed a 512 × 512 image. Two hiding capacities were achieved by using two different numbers of symbols, as previously mentioned. Using 16 symbols, the technique achieved good average PSNR values for both PSNR1 and PSNR2 with an average PSNR of 51.60 dB for the same data hiding capacity of 524,288 bits. With 25 symbols and the exact same technique, the embedding capacity was increased to 608,174 bits, which is greater than the hiding capacity of other existing techniques. [ABSTRACT FROM AUTHOR]

For image steganography, it is necessary to improve the quality of the reconstructed image and stego image as high as possible while maintaining the security of the system. To achieve this goal, we propose a novelty image steganography via deep-based compressive sensing (CS) for the reconstructed image and directional lifting wavelet transform (DLWT) for the stego image. The plain image is first randomly under-sampled and diffused by the measurement matrix and simulated noise to generate the secret image. And the above two matrices were created using a logistic map with two initial values. Then, we embed the secret image into the DLWT domain of the carrier image by singular value decomposition (SVD), resulting in the meaningful stego image. Finally, for enhancing the quality of the reconstructed image from the extracted secret image, we present the deep-based CS reconstruction algorithm. Experimental results verify the effectiveness that the proposed scheme can achieve visual quality, robustness, and security. [ABSTRACT FROM AUTHOR]

The rapid development of the Internet of Things has opened up commercial and economic opportunities, but there are also risks and threats to cybersecurity: a significant amount of private data is exposed in an untrusted cyberspace. In view of this issue, the research on reversible data hiding in encrypted image (RDHEI) aims to establish a secure and private communication channel between a sender and a recipient by embedding data into encrypted images. Therefore, this paper proposes a novel RDHEI scheme that employs a Huffman-based lossless image coding technique to achieve a high embedding capacity. Specifically, we compress the original image into a bitstream through the JPEG-like compression and then further encode the difference values between the reconstructed JPEG image and the original image via the Huffman coding. Due to the high compression rate and coding efficiency of the combined strategy, a large embedding space can be created. Our proposed scheme not only ensures a lossless recovery of the original image but also an error-free extraction of the secret messages. Several experiments are conducted to verify that our proposed scheme achieves a state-of-the-art performance compared with the prior art in terms of embedding capacity. [ABSTRACT FROM AUTHOR]

Digital watermarking technology is an important means to effectively protect three-dimensional (3D) model data. Among them, "blind detection" and "robustness" are key and difficult points in the current research of digital watermarking technology based on 3D models. In order to realize the blind detection of a watermark and improve its robustness against various common attacks at the same time, this paper proposes a dual blind watermarking method based on the normal feature of the centroid of first-ring neighboring points. The local spherical coordinate system is constructed by calculating two different normal vectors, and the first pattern watermark and the second random binary sequence watermark are embedded, respectively. The experimental results show that this method can not only realize the blind detection of dual watermarks, but also have the ability to resist common attacks such as translation, rotation, scaling, cropping, simplification, smoothing, noise, and vertex reordering to a certain extent. [ABSTRACT FROM AUTHOR]

Data security is very essential since the communication takes place in the open network. In order to protect the data techniques such as image encryption and data hiding have become very popular. In this paper, a Reversible Data Hiding (RDH) based on combination of optimization algorithm, image interpolation and encryption techniques is proposed to achieve high quality of stego-images and security. Initially, the input cover image is taken and divided into 2 × 2 blocks and edges in the images are identified using edge detection techniques. Next, optimization algorithm is developed to find optimal pixels which improve the performance. Then, the interpolation process is applied to up-scale the image based on optimal pixel. Data is hidden in the interpolated pixels using dual capacity predictions method and finally image is encrypted based on edge, non-edge and interpolated pixels is sent to the receiver. Experimental results demonstrate that the proposed scheme outperforms the state-of-the-arts in terms of image quality performance, embedding capacity and Universal Image Quality Index (UIQI). Furthermore, the proposed solution is resistant to security analysis based on Structural Similarity Index Measure (SSIM) and Regular Singular (RS) analysis. [ABSTRACT FROM AUTHOR]

Although traditional reversible data hiding (RDH) methods work well at protecting the secret data and guaranteeing the high visual quality of the cover image as well, the performance of down steaming visual tasks, such as feature extraction and point alignment, is degraded. To address this issue, Hou et al. [13] proposed to embed secret data into color images while keeping the corresponding grayscale invariant. However, we find that the embedding efficiency of this method is still unsatisfactory. And the embedding distortion should be further reduced. In this paper, unit embedding distortion is designed to help evaluate the embedding efficiency of per pixel unit. Then, an adaptive embedding pattern is introduced by adaptively embedding one or two bits of secret data into different positions according to the context information. While our approach provides a novel two-level predictor, benefiting from two normal predictors to reduce the embedding distortion. Experimental results demonstrate that, compared to the previous method, our scheme could significantly enhance the image fidelity while keeping the grayscale invariant. [ABSTRACT FROM AUTHOR]