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As the number of people using the Internet has increased, more information is stored and accessible daily. As a result, the requirement for information security also grows. In the early stages of data security, cryptography is used. Cryptography turns readable information into an unreadable form. Steganography is the next generation of information security. The main downside of this steganography is that the digital media becomes damaged due to hiding information in digital media. The next stage of information security is Reversible Data Hiding (RDH). This method can restore personal information and digital media without error. The next method, Separable Reversible Data Hiding in Encrypted Digital Media, recovers the digital media and extracts concealed information independently without disturbing or knowing each other. This paper presents a novel Separable Reversible Data Hiding by Vacating Room After Encryption using the Encrypted Pixel Difference (SRDH-VRAE-EPD) method, which combines homomorphic encryption and encrypted pixel differences. The proposed method offers the following advantages. It achieves an embedding rate of 1.2 bpp, significantly improving upon standard VRAE algorithms while allowing for lossless data extraction and image recovery. The encrypted image ensures high security against various attacks, including statistical, differential, and chosen plaintext attacks, and it allows for the extraction of secret data and recovery of the original image independently, making it a separable process.

The conventional histogram-based reversible data-hiding scheme is one-dimensional (1D). In this article, a novel framework that can be used to design 2D reversible data-hiding schemes is presented. Through the flexibility of selecting peaks for each channel, this 2D technique offers higher embedding performance than the conventional 1D techniques. For illustration, the framework is applied to develop two new schemes, C-2D and S-2D. Compared with the 1D schemes that use the predictions individually, the experimental results show that C-2D and S-2D have apparent performance advantages. This framework can be applied to any architecture. Furthermore, it can be easily extended into a multi-dimensional framework. By combining appropriate prediction methods, more reversible data-hiding schemes can be derived.

In this paper, we propose a new framework for reversible data hiding in encrypted images, where both the hiding capacity and lossless compression efficiency are flexibly controlled. There exist two main purposes; one is to provide highly efficient lossless compression under a required hiding capacity, while the other is to enable us to extract an embedded payload from a decrypted image. The proposed method can decrypt marked encrypted images without data extraction and derive marked images. An original image is arbitrarily divided into two regions. Two different methods for reversible data hiding in encrypted images (RDH-EI) are used in our method, and each one is used for either region. Consequently, one region can be decrypted without data extraction and also losslessly compressed using image coding standards even after the processing. The other region possesses a significantly high hiding rate, around 1 bpp. Experimental results show the effectiveness of the proposed method in terms of hiding capacity and lossless compression efficiency.

The existing data hiding schemes conceal the data in the cover image and then communicate secretly on the channel. The weakness of these methods is that the security aspect is somewhat lacking, and there is a limit to hiding enough data. In this paper, we propose a reversible data hiding method based on dual AMBTC images. It improves security, which is a weakness of data hiding. AMBTC has strengths in low-bandwidth channel environments with simple calculations and efficient data performance. HC(7,4) and LSB replacement methods are applied to each block of AMBTC to hide secret data. After the embedding process, the two AMBTC-marked images are obtained, and these images are sent to different recipients. The recipients can extract hidden messages and restore the cover AMBTC image by using the proposed method and two marked images. Our proposed data hiding method guarantees sufficient data hiding, proper cover image quality, and restoration of the original cover image. Experimental results show that our method is efficient in terms of image quality and embedding ratio.

We propose an integrated model of Block-Permutation-Based Encryption (BPBE) and Reversible Data Hiding (RDH). The BPBE scheme involves four processes for encryption, namely block scrambling, block-rotation/inversion, negative-positive transformation and the color component shuffling. A Histogram Shifting (HS) method is adopted for RDH in our model. The proposed scheme can be well suitable for the hierarchical access control system, where the data can be accessed with the different access rights. This scheme encrypts R, G and B components independently. Therefore, we can generate similar output images from different input images. Additionally, the key derivation scheme also provides the security according to the different access rights. Our scheme is also resilient against brute-force attacks and Jigsaw Puzzle Solvers (JPSs). Furthermore, the compression performance is also not severely degraded using a standard lossless compression method.

Reversible data hiding in encrypted images has become an effective and popular way to preserve the security and privacy of users’ personal images. Recently, Xiao et al. firstly presented reversible data hiding in encrypted images with use of the modern signal processing technique compressive sensing (CS). However, the quality of decrypted image is not great enough. In this paper, a new method of separable data hiding in encrypted images are proposed by using CS and discrete fourier transform, which takes full advantage of both real and imaginary coefficients for ensuring great recovery and providing flexible payload. Compared with the original work, the proposed method can obtain better image quality when concealing the same embedding capacity. Furthermore, image decryption and data extraction are separable in the proposed method, and the secret data can be extracted relatively accurately.

With the proliferation of image-capturing and display-enabled IoT devices, ensuring the authenticity and integrity of visual data has become increasingly critical, especially in light of emerging cybersecurity threats and powerful generative AI tools. One of the major challenges in such sensor-based systems is the ability to protect privacy while maintaining data usability. Reversible data hiding has attracted growing attention due to its reversibility and ease of implementation, making it a viable solution for secure image communication in IoT environments. In this paper, we propose reversible data hiding techniques tailored to the content characteristics of images. Our approach leverages subsampling and quadtree partitioning, combined with multi-stage prediction schemes, to generate a predicted image aligned with the original. Secret information is embedded by analyzing the difference histogram between the original and predicted images, and enhanced through multi-round rotation techniques and a multi-level embedding strategy to boost capacity. By employing both subsampling and quadtree decomposition, the embedding strategy dynamically adapts to the inherent characteristics of the input image. Furthermore, we investigate the trade-off between embedding capacity and marked image quality. Experimental results demonstrate improved embedding performance, high visual fidelity, and low implementation complexity, highlighting the method’s suitability for resource-constrained IoT applications.

In the most existing reversible data hiding schemes for encrypted images, cover images can be reversibly recovered, but the integrity of image content cannot be guaranteed. This paper proposes a reversible data hiding and authentication scheme for encrypted images to implement reversible recovery and content authentication of cover images and secret data. The content owner employs a new predictor ISGAP to generate more accurate predictions and smaller errors. The errors are then compressed with adaptive Huffman coding to enlarge the embedding space, and the plaintext authentication information is embedded in it. The data hider embeds secret data into the encrypted image along with ciphertext authentication information. The receiver performs ciphertext authentication first and then implements cover recovery and plaintext authentication according to different keys. Experiments were carried out with 100 images selected from each dataset of BOSSbase and BOWS-2, and the results show that the scheme has higher embedding capacity and can effectively implement image content authentication while ensuring high security and reversible recovery.

The goal of this survey is to review the state-of-the art Reversible Data Hiding (RDH) methods, classify these methods into different classes, and list out new trends in this field. RDH, in general, is a challenging problem and has potential applications in the today’s digital world. Reversible data hiding methods not only securely transfer secret data but also recover the cover media faithfully. Recently, RDH methods are mainly focused on obtaining high capacity along with tuneable quality. Although, extensive investigations in the field of reversible data hiding was carried out in the recent past, a comprehensive review of existing literature for listing out research gap and future directions has not yet been reported. In this survey, we have classified the reversible data hiding methods mainly into a) Plain domain b) Encrypted domain and also examine their pro and cons. Tabular comparison of various RDH methods has been provided considering various design and analysis aspects. Moreover, we discuss important issues related to reversible data hiding and use of benchmarked datasets along with performance metrics for evaluation of RDH methods.

A novel local binary pattern‐based reversible data hiding (LBP‐RDH) technique has been suggested to maintain a fair symmetry between the perceptual transparency and hiding capacity. During embedding, the image is divided into various 3×3 blocks. Then, using the LBP‐based image descriptor, the LBP codes for each block are computed. Next, the obtained LBP codes are XORed with the embedding bits and are concealed in the respective blocks using the proposed pixel readjustment process. Further, each cover image (CI) pixel produces two different stego‐image pixels. Likewise, during extraction, the CI pixels are restored without the loss of a single bit of information. The outcome of the proposed technique with respect to perceptual transparency measures, such as peak signal‐to‐noise ratio and structural similarity index, is found to be superior to that of some of the recent and state‐of‐the‐art techniques. In addition, the proposed technique has shown excellent resilience to various stego‐attacks, such as pixel difference histogram as well as regular and singular analysis. Besides, the out‐off boundary pixel problem, which endures in most of the contemporary data hiding techniques, has been successfully addressed.