Reversible Data Hiding In Encrypted Images Research Articles

Encrypted image processing using compression and reversible data hiding

Reversible data hiding within encrypted images reversible data hiding in encrypted images (RDH-EI) is a highly effective technique for image processing in the field of encryption. This paper, propose a RDH-EI technique, which utilizes bit-plane compression and various image scanning directions to generate vacant space for data embedding, referred to as vacating room. Initially, the prediction error of the pre-processed image is computed. Subsequently, each bit-plane image is converted into a bit-stream by following the pixel scan order employed before compression. The compressed image is then encrypted employing a stream cipher. Through the process of substitution, the secret data and additional information are incorporated into the acquired image without any knowledge of the original content or the encrypted key. Finally, the generated image is transmitted or archived. The experiments provide evidence that the proposed method surpasses the most advanced methods currently available.

Secure Reversible Data Hiding in Encrypted Image Based on 2D Labeling and Block Classification Coding

The existing lossless compression methods in reversible data hiding in encrypted images (RDHEI) do not fully utilize pixel and local redundancy, and encryption methods can not resist various attack algorithms. To solve the above problem, a secure RDHEI algorithm based on 2D labeling and block classification coding is proposed. In the proposed RDHEI algorithm, the retained total LSB (least significant bit) data as the image feature in the mixed permutation to generate the encryption key that varied with image, which improves the security of the algorithm. In addition, 2D labeling and block classification coding are designed. The former improves the utilization of pixel redundancy by labeling the length of the first ‘0’ string and the next ‘1’ string in the predicted value. The latter effectively utilizes the local correlation of the image, reduces the number of label values in the smooth block, so the length of the compressed coding stream is reduced. The combination of 2D labeling and block classification coding effectively improves the capacity. Experimental results show that the proposed method can effectively resist statistical, known plaintext and differential attacks, and the average capacity of three databases is 0.41bpp higher than the state-of-the-art algorithms.

Secret Sharing Based Reversible Data Hiding in Encrypted Image with Multiple Data Hiders

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

Reversible data hiding in encrypted images with multi-prediction and adaptive huffman encoding

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.

Cryptanalysis of iterative encryption and image sharing scheme based on the VQ attack

Reversible data hiding in encrypted images (RDHEI) is widely employed to protect privacy in images stored on cloud storage. Recently, Yu et al. [22] proposed an effective image encryption scheme called iterative encryption and image sharing (IEIS), which is highly compatible with RDHEI. In this study, we analyze the characteristics of IEIS and present a cryptanalysis scheme based on vector quantization (VQ) attack. To capture the pixel-changing pattern of an image block, the concept of pixel difference matrix (PDM) is introduced. VQ attack is subsequently utilized to estimate the ciphertext block. Furthermore, we employ a well-trained convolutional neural network (CNN) based discriminator to identify the proper block permutation sequence within the secret key space. Experimental results demonstrate the efficacy of our proposed cryptanalysis scheme. Based on our study, we conclude that the IEIS scheme raises security concerns.

High capacity reversible data hiding with contiguous space in encrypted images

Reversible data hiding in encrypted images (RDHEI) is used to embed secret data into an encrypted image to ensure data security and image privacy. However, a considerable portion of the existing methods do not achieve a high data embedding rate (ER) with complete reconstruction of the original image. Considering the aforementioned limitation, this paper proposes a new RDHEI method with contiguous space. The proposed method pre-processes the original image by dividing it into non-overlapping blocks to determine a label map based on absolute prediction errors. Next, the label map is encoded, and bit-plane shifting is done to create contiguous space for embedding. Thus, the proposed method effectively exploits local and overall image spatial correlation and creates a larger space for embedding in a bit-plane-wise manner. Compared to the state-of-the-art methods, the ER of the proposed method is significantly increased while ensuring complete reversibility and lossless extraction of the hidden data.

Adaptive embedding combining LBE and IBBE for high-capacity reversible data hiding in encrypted images

Reversible data hiding in encrypted image (RDHEI) has received wide attention as an effective information protection technique, and most of the existing RDHEI schemes introduce pixel prediction technique to improve embedding performance. However, the high embedding capacity (EC) requirement is still not achieved because the redundancy of carrier medium is not fully utilized. Thus, a novel RDHEI based on pixel prediction and adaptively combining "L"-shaped block embedding (LBE) and improved binary-block embedding (IBBE) is presented, which maximizes the use of Laplacian-like distribution of prediction-errors to achieve higher EC. Specifically, the original image is first predicted to get the prediction-error image and then eight binary prediction-error bit-planes (PEBPs) are generated. Subsequently, the proposed LBE and IBBE are used to calculate the net EC to encode each PEBP. Also, a new bit-plane selection encryption is designed to ensure that the intra-block correlations of the IBBE-based PEBPs remain unchanged. Eventually, the data hider adaptively completes data embedding according to the PEBP coding. Moreover, the 4-D hyperchaotic system is exploited to encrypt the carrier image and the secret data to further enhance the security. Extensive experimental results verify that our strategy achieves more outstanding performance compared with some state-of-the-art schemes.

Reversible Data Hiding With Hierarchical Block Variable Length Coding for Cloud Security

Reversible data hiding in encrypted images (RDHEI) can serve as a technical solution to secure data in applications that rely on cloud storage. The key features of an RDHEI scheme are reversibility, security, and data embedding rate. To enlarge the embedding rate, this paper proposes a novel RDHEI scheme based on the median edge detector (MED) and a new proposed hierarchical block variable length coding (HBVLC) technique. In our scheme, the image owner first predicts the pixel values of the carrier image with MED. Then, the prediction error array is sliced into bit-planes and encoded plane by plane. By leveraging the inherent features of the prediction error bit-planes, the image owner adaptively decomposes a bit-plane into blocks of different hierarchical levels based on its local smoothness and encodes the blocks with a variable length coding method. As a result, the carrier image is efficiently compressed to provide spare room for data embedding. The encoded carrier image is then processed with the conventional steps of an RDHEI technique. Experimental results show that the proposed scheme not only can restore the secret data and the carrier image without loss but also outperforms state-of-the-art methods in the embedding rate for images with various features.

High-Capacity Reversible Data Hiding in Encrypted Images Based on 2D-HS Chaotic System and Full Bit-Plane Searching

Using the local correlation of carrier images to embed secret data in MSBs is a popular scheme for reversible data hiding in encrypted images (RDHEI). However, most existing methods based on this scheme face challenges in achieving complete compression while ensuring security. In this study, an RDHEI method that uses a two-dimensional chaotic system and full bit-plane search (FBPS) is proposed. Specifically, the content owner provides cover images and employs a chaotic system to generate chaotic sequences for inter-block non-symmetrical permutation and intra-block diffusion. The special encryption method, combined with chaos, not only preserves the correlation of pixels within a block but also ensures an extremely high level of security. The FBPS technique is applied to detect all smooth bit planes, not limited to continuous MSBs. For data embedding, ‘0’ and ‘1’ are used to record all smooth and rough bit planes to achieve thorough compression. The results of the experiment show that our proposed method provides a high level of security and achieves 2.142 bit/pixel and 2.339 bit/pixel on the typical datasets BOSSbase (Break Our Steganographic System) and BOWS-2 (Break Our Watermarking System 2nd). Compared with the state-of-the-art methods, the embedding capacity has also been significantly improved.

Reversible data hiding in encrypted image using two-pass pixel value ordering

In recent years, reversible data hiding in encrypted images (RDHEI) has gained popularity as it enables the concealing of confidential information in anonymized host image. Because of this, conventional reversible data hiding (RDH) methods that utilize the spatial correlation of natural host images cannot be employed in RDHEI where the embedding is done in the encrypted image without reserving a room. To address this concern, this paper proposes a new RDHEI method based on popular pixel value ordering (PVO) strategy of the conventional high fidelity RDH. For this, the image pixels are first encrypted in blocks using novel difference-preserving encryption for maintaining the original difference among the pixels of each block. Next, a two-pass PVO (TPPVO) is employed for embedding. The TPPVO first sorts the pixels and then performs the embedding in two passes in such a way that high embedding capacity (EC) can be obtained while also ensuring reversibility. Experimental evaluations also demonstrate that the proposed TPPVO-RDHEI not only enlarges the EC approximately by 0.1130 bpp and 0.01 bpp for the smooth and complex images, respectively in comparison to the best performing related method, but also maintain the visual security while ensuring the complete reversibility.

Reversible Data Hiding in Shared Images Based on Syndrome Decoding and Homomorphism

Reversible Data Hiding in Encrypted Images (RDHEI) has drawn increasing concern in multimedia cloud computing scenarios. It embeds secret message into the encrypted carrier while preserving the confidentiality of the image. However, most RDHEI schemes have only one hider and one image carrier which are not efficient for the distributed system with multiple participants. Moreover, if the stego-image is lost, the cover image and the embedded data cannot be restored. To solve above issues, this paper proposes Reversible Data Hiding in Shared Images based on syndrome decoding and homomorphism (RDHSI). In RDHSI, the cover image and secret data are distributed using secret sharing. Multiple data hiders embed shared data into the shared images based on the Syndrome Decoding of Hamming codes and the additive homomorphism of the polynomial. On the receiver side, the lossless cover image and secret data are obtained. The reversibility and privacy preserving of the cover image, the complete extraction of secret data, and the fault-tolerance of the proposed schemes are achieved. The experimental results show that PSNR of the marked image is above 54 dB at the embedding rate of 0.43 <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">bpp</i> . In order to improve the payload of secret data, the Modified RDHSI is further proposed. Generally, the proposed schemes are secure, effective and fault-tolerant.

Visually meaningful image encryption combining with reversible data hiding in encrypted images

At present, most image encryption schemes directly change plaintext images into ciphertext images without visual significance, such ciphertext images can be detected and therefore subject to various attacks. To protect the content security and visual safety of images, a visually meaningful image encryption (VMIE) algorithm combining with Reversible Data Hiding in Encrypted Images (RDHEI) is proposed. First, the secret image is encrypted and additional information is embedded by Chen hyperchaotic system and prediction error expansion (PEE) method. Then the source image is encrypted by a Lorentz hyperchaotic system. Finally, bit-xor operation is performed on the resulting encrypted image and the result is saved in a cloud database to generate an indexing key using SHA-256,which enables the receiver to recover the secret image with the resource image and the key alone. The scheme combines with the RDHEI, improving the transmission efficiency and has no image quality problems.The experimental results and security analysis show that the image encryption scheme has sufficient key space, strong key sensitivity and wide applicability.

Lossless Reversible Data Hiding in Encrypted Image for Multiple Data Hiders Based on Pixel Value Order and Secret Sharing

Reversible data hiding in encrypted images (RDH-EI) is instrumental in image privacy protection and data embedding. However, conventional RDH-EI models, involving image providers, data hiders, and receivers, limit the number of data hiders to one, which restricts its applicability in scenarios requiring multiple data embedders. Therefore, the need for an RDH-EI accommodating multiple data hiders, especially for copyright protection, has become crucial. Addressing this, we introduce the application of Pixel Value Order (PVO) technology to encrypted reversible data hiding, combined with the secret image sharing (SIS) scheme. This creates a novel scheme, PVO, Chaotic System, Secret Sharing-based Reversible Data Hiding in Encrypted Image (PCSRDH-EI), which satisfies the (k,n) threshold property. An image is partitioned into N shadow images, and reconstruction is feasible when at least k shadow images are available. This method enables separate data extraction and image decryption. Our scheme combines stream encryption, based on chaotic systems, with secret sharing, underpinned by the Chinese remainder theorem (CRT), ensuring secure secret sharing. Empirical tests show that PCSRDH-EI can reach a maximum embedding rate of 5.706 bpp, outperforming the state-of-the-art and demonstrating superior encryption effects.

Reversible Data Hiding in Encrypted Image via Joint Encoding of Multiple MSB and Pixel Difference

Reversible data hiding in encrypted image (RDHEI) has become a research hotspot, which can effectively protect image content privacy. An RDHEI scheme based on the joint encoding of multiple MSBs (most significant bits) and pixel difference is proposed in this paper. A block-based image encryption method is adopted on the content owner side, which can securely protect the image contents while retaining the spatial correlation within each block. By the joint encoding strategy of multiple MSB and pixel difference, the redundancy within the bit plane is sufficiently compressed to accommodate more additional data; thus, a high embedding rate can be achieved. According to different kinds of available keys, image decryption and data extraction can be separably conducted on the receiver side. Experimental results show that our scheme can achieve a higher embedding rate than some state-of-the-art schemes.

Efficient lossless based secure communication in 6G Internet-of-Things environments

Future sustainable energy-efficient computing solutions in e-healthcare, smart cities, and intelligent robotics applications provide the many benefits and real-time services made possible by the Internet of Things (IoT) and the cloud computing platform. IoT is a relatively new technology expected to emerge due to the expansion of data, communication channels, and embedded systems. Through the IoT, users and physical objects exchange data and interact on virtual networks. Due to the resource-constraint nature of IoT, it is becoming increasingly difficult for organizations and individuals to protect their private information as the value of digital information rises. Reversible Data Hiding (RDH) in Encrypted Images (RDHEI) is gaining popularity in 6G technology for privacy protection because of its ability to embed secret data within an encrypted image and confirm the hidden information authenticity. In this research, we proposed a sustainable, energy-efficient, multi-MSB (most significant bit)-based dynamic quadtree partition with enhanced Huffman coding. Different prediction representations are also utilized to anticipate the existing pixel value from the adjacent pixels based on quadtree partitions to take greater advantage of the spatial association in the cover image. Furthermore, the freed-up large space is used to insert additional data using dynamic quadtree partitions to encrypt the image. Our approach has an optimum embedding capacity compared to the current state-of-the-art schemes.

A Universal Reversible Data Hiding Method in Encrypted Image Based on MSB Prediction and Error Embedding

Image encryption is used for privacy protection in cloud computing. Nowadays, reversible data hiding in encrypted image (RDHEI) has achieved great success with the demand of embedding additional information into encrypted image. The existing algorithms cannot implement large embedding capacity and good reconstructed image quality simultaneously. Besides, the universality of some methods is limited when they are used in images with different textural characteristics. In this work, an RDHEI method based on most significant bit (MSB) prediction and error embedding is proposed. On one hand, all types of prediction errors are considered in the proposed method, therefore all the pixels with prediction errors can be recovered correctly. On the other hand, error blocks are utilized to mark the locations of prediction errors and message blocks are utilized to embed data. Moreover, flag blocks are utilized to distinguish error and message blocks. To solve the problem of misjudgement for flag blocks in the decoding phase, special operations are conducted on error blocks and message blocks. Experimental results demonstrate that, compared with the state-of-the-art RDHEI methods, the proposed method has good universality on well-known databases.

Reversible Data Hiding in Encrypted Images with Extended Parametric Binary Tree Labeling

Images uploaded to the cloud may be confidential or related to personal private information, so they need to be encrypted before uploading to the cloud storage. At the service provider side, appending additional information is usually required for transmission or database management. Reversible data hiding in encrypted images (RDHEI) serves as a technical solution. Recent RDHEI schemes successfully utilize the spatial correlation between image pixel values to vacate spare room for data hiding, however, the data payload can be further improved. This paper proposes a RDHEI scheme based on extended parameter binary tree labeling, which replaces non-reference pixel values with their prediction errors in a reduced length to vacate space. We further encode the prediction error of non-embeddable pixels to fit the space left from labeling. Thus, the space required to store the pixel bits replaced by labeling codes is saved. Experimental results show that the data payload of the extended parametric binary tree labeling outperforms state-of-the-art schemes. The embedding rates for the commonly applied datasets, including Bossbase, BOWS-2, and UCID, are 3.2305 bpp, 3.1619 bpp, and 2.8113 bpp, respectively.

Odd-even discrimination-based reversible data hiding technique in encrypted images

Here, we describe a new method for reversible data hiding in encrypted images (RDHEI) that aims to improve the embedding capacity (EC) and visual quality of the stego image. Most of the existing techniques for RDHEI need location maps to discriminate embedded and non-embedded pixels, which increases computational overhead and affects EC. The proposed method reserves room after encryption and converts prediction errors (PE) to odd and even numbers to discriminate between embedded and non-embedded pixels. This avoids the computational overhead caused by the use of a location map. The proposed scheme also employs double-layer encryption using random permutation and a stream cipher to secure the cover images. The method is separable, which means that the secret data and cover image can be independently extracted and recovered, depending on the availability of the data hiding and decryption keys. The scheme uses block-wise reference pixels for the calculation of PE, that enhances the EC. Experimental results indicate that the proposed scheme is more effective than existing state-of-the-art works.

Reversible Data Hiding in Palette Images

Reversible data hiding (RDH) has been investigated for over two decades. Depending on the application scenario, it can be divided into RDH and reversible data hiding in encrypted images (RDHEI). Interestingly, almost all studies on RDH/RDHEI have been conducted on gray-scale images, and relatively few studies have been conducted on color images compared to those on gray-scale images. Moreover, very few studies have been undertaken on palette images as a widely used image format. For palette images in which pixels are not gray-scale levels but color table indexes, it is difficult to apply traditional RDH/RDHEI methods directly. Therefore, we propose a new framework for RDH/RDHEI specifically for palette images. This framework adds a route selection algorithm before the conventional RDH/RDHEI approach. To be specific, we propose a method named the shortest route with correlation and frequency selection to reorder the color table, followed by a correlation reconstruction of the remapped index image according to this color table. The experimental results show the improvement brought by our proposed route selection to the existing RDH/RDHEI methods in palette images.

Reversible Data Hiding in Encrypted Image Using Multiple Data-Hiders Sharing Algorithm

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