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

Приводятся результаты экспериментального исследования обратимого алгоритма сокрытия данных в зашифрованных изображениях, использующего код Хэмминга (7,4) и MSB-прогнозирования, который был разработан на основе алгоритма китайских исследователей Каймен Чена и Чин-Чен Чанга и реализован на языке программирования С#. The article presents the results of an experimental study of one reversible algorithm for hiding data in encrypted images using (7,4) Hamming code and MSB prediction, which was developed based on the algorithm of Chinese researchers Kaimeng Chen and Chin-Chen Chang and implemented in the C# programming language.

Reversible data hiding in encrypted image (RDHEI) is a technique that can be adopted by cloud sever to embed additional data into the encrypted image with no permanent distortion. For RDHEI, it remains a challenging task to improve the embedding capacity under the premise of real reversibility. In this paper, a novel RDHEI method based on adaptive most significant bit (MSB) prediction is proposed. The cover image is first encrypted in block-wise manner such that the correlation of pixels within block is preserved. After that, all blocks are permuted to fulfill the final encryption. During data embedding, the upper-left pixel within block is used to predict others such that the embedding room is vacated. Then, available blocks are selected and all blocks are rearranged so as to ensure reversibility. By fully exploiting the correlation of pixels within block via adaptive MSB prediction, the proposed method successes to achieve desirable improvement in capacity. Experimental results show that the proposed method significantly outperforms previous methods. Moreover, real reversibility and real separability are also guaranteed. In a word, the proposed method is a practical method that can be adopted by cloud storage

Reversible data hiding in encrypted domain (RDH-ED) technology can embed data into cover media without exposing the original content to third parties. In addition, the recipient can recover the cover media losslessly after extracting the embedded data. Image-based RDH-ED has been widely studied, but RDH-ED based on 3D meshes has obtained few research results due to the complex data structure and irregular geometric structure of 3D meshes. With the widespread application of 3D meshes, the research on 3D meshes has attracted extensive research from researchers in recent years. In this paper, we propose a reversible data hiding for encrypted 3D meshes based on integer mapping and most significant bit (MSB) prediction. The content owner divides all vertices into “embedded” sets and “reference” sets and then maps floating-point coordinates to integers. After calculating the MSB prediction error of the “embedded” sets, the encryption technology is performed. Then, additional data can be embedded through the MSB replacement strategy. According to different permissions, legal recipients can obtain the original meshes, the additional data or both of them by using the proposed separable method. Higher embedding capacity is achieved by adopting MSB embedding strategy, and perfect recovery of the original meshes is achieved by using ring prediction scheme. The experimental results show that the proposed method has greater embedding capacity compared with the state-of-the-art method.

The reversible data hiding in encrypted images by MSB prediction of P. Puteaux and W. Puesch not only provides high embedding bit-rates, but also entails a very low mathematical complexity. This correspondence investigates its security and shows flaws in embedding imperceptibility, unauthorized detection/removal of embedded data and unauthorized access to image content. Secure solutions are discussed.

In this paper, we extend a high-capacity reversible data hiding method in encrypted images to fully ensure the reversibility and enhance the payload capacity. For the perfect reversibility, marker bits are inserted into a payload depending on the length of flag, which separates available pixels for data hiding from non-available pixels. Owing to modifying the MSB prediction error highlighting, the hiding capacity is enhanced in the proposed method. We further introduce the serpentine scan order in the prediction error detection, leading to the hiding capacity being further improved.

As a new generation of digital media for covert transmission, three-dimension (3D) mesh models are frequently used and distributed on the network. Facing the huge massive of network data, it is urgent to study a method to protect and store this large amounts of data. In this paper, we proposed a high capacity reversible data hiding in encrypted 3D mesh models. This method divides the vertices of all 3D mesh into "embedded sets" and "prediction sets" based on the parity of the index. In addition, the multiple most significant bit (Multi-MSB) prediction reserved space is used to adaptively embed secret message, and the auxiliary information is compressed by arithmetic coding to further free up redundant space of the 3D mesh models. We use the majority voting system(MSV) principle to restore the original mesh model with high quality. The experimental results show that our method achieves a higher embedding capacity compared with state-of-the-art RDH-ED methods on 3D mesh models and can restore the original 3D mesh models with high quality., Comment: Published in Signal Processing

This paper proposes a new most significant bit (MSB)-prediction switching scheme and presents an energy-efficient successive approximation register (SAR) analog-to-digital converter (ADC) using the proposed scheme. The prediction of the MSB is conducted before the sampling phase, and the MSB-1 conversion switches all the capacitors of the capacitive digital-to-analog converter (CDAC) from the references set by the prediction result after the sampling phase. Therefore, the reference voltage in the proposed scheme is reduced by half to satisfy the same input range. Compared with the regular Vcm-based CDAC, the proposed technique exhibits a 75.1% reduction in switching energy and a reduction ratio of (1/2)1/2 in nonlinearity under the same capacitor area and matching condition. A 10-bit SAR ADC prototype is designed and simulated in a 180-nm CMOS process to validate the proposed technique. The ADC consumes $31.16~\mu \text{W}$ from a 1-V supply and the input range of [−2 V, 2 V]. The simulated signal-to-noise-and-distortion ratio is 61.01 dB at 2 MS/s, benefited from the redundant capacitors added to the CDAC.

In this paper, a most significant bits (MSBs) prediction strategy for the design of successive approximation register (SAR) analog-to-digital converter (ADC) in battery pack voltage detection is proposed to reduce conversion time without losing accuracy. The strategy takes advantage of the battery pack voltages characteristics where there is a strong correlation among neighboring cell voltage values. By generating the MSBs with the quantization results of the battery pack in the previous loop, the ADC just needs to convert the remaining least significant bits (LSBs). This paper analyzes the relationship between saved time and five parameters: reading frequency (f), cell number of battery pack (N), cell number (CN) for MSB-prediction, standard deviation (σ), change rate of digital number (K), which can give a feasible prediction on saved working time in any conditions. With this strategy, in a f = 50 kHz, N = 10, CN = 8, σ = 10 system, up to 27.83% A/D conversion time can be saved in charging state, and 27.89% A/D conversion time can be saved in discharging state.

International audience; In the last few years, visual privacy has become a major problem. Because of this, encrypted image processing has received a lot of attention within the scientific and business communities. Data hiding in encrypted images (DHEI) is an effective technique to embed data in the encrypted domain. The owner of an image encrypts it with a secret key and it is still possible to embed additional data without knowing the original content nor the secret key. This secret message can be extracted and the initial image can be recovered in the decoding phase. Recently, DHEI has become an investigative field, but the proposed methods do not allow a large amount of embedding capacity. In this paper, we present a new method based on the MSB (most significant bit) prediction. We suggest to hide one bit per pixel by pre-processing the image to avoid prediction errors and, thereby, to improve the quality of the reconstructed image. We have applied our method to various images and, in every cases, the obtained image is very similar to the original one in terms of PSNR or SSIM.

Reversible data hiding in encrypted images is an effective technology to embed additional data in the encrypted domain without accessing the content of the original image. During the decoding process, the secret message can be extracted accurately and the original image can be reconstructed perfectly. In this paper, an efficient reversible data hiding scheme for encrypted images based on MSB (most significant bit) prediction is proposed, which has high embedding capacity. Combining with the characteristic of prediction technology, the prediction error is first identified and its location is stored in the location map. The stream cipher is then used to encrypt the original image. According to the location map, the data-hider substitutes up to three MSBs of embeddable pixels in encrypted image with the secret message. At the receiving end, the secret message can be extracted without error, and the original image can be perfectly reconstructed by utilizing MSB prediction technology. Experimental results show that the scheme can achieve higher embedding capacity than most related methods.

Nowadays, more and more researchers are interested in reversible data hiding in encrypted images (RDHEI), which can be applied in privacy protection and cloud storage. In this paper, a new RDHEI method on the basis of hierarchical quad-tree coding and multi-MSB (most significant bit) prediction is proposed. The content owner performs pixel prediction to obtain a prediction error image and explores the maximum embedding capacity of the prediction error image by hierarchical quad-tree coding before image encryption. According to the marked bits of vacated room capacity, the data hider can embed additional data into the room-vacated image without knowing the content of original image. Through the data hiding key and the encryption key, the legal receiver is able to conduct data extraction and image recovery separately. Experimental results show that the average embedding rates of the proposed method can separately reach 3.504 bpp (bits per pixel), 3.394 bpp, and 2.746 bpp on three well-known databases, BOSSBase, BOWS-2, and UCID, which are higher than some state-of-the-art methods.

Reversible data hiding in encrypted domain (RDH-ED) has received tremendous attention from the research community because data can be embedded into cover media without exposing it to the third party data hider and the cover media can be losslessly recovered after the extraction of the embedded data. Although, in recent years, extensive studies have been carried out about images based RDH-ED, little attention is paid to RDH-ED in 3D meshes due to its complex data structure and irregular geometry. In this paper, we propose a separable RDH-ED method for 3D meshes based on integer mapping and Multi-MSB (multiplication most significant bit) prediction. The proposed method divides all the vertices of the mesh into the "embedded" set and "reference" set, and maps decimals of the vertex into integers. Then, we calculate the Multi-MSB prediction errors for the vertices of the "embedded" set and a bit-stream encryption technique will be executed. Finally, additional data is embedded by replacing the Multi-MSB of the encrypted vertex coordinates. According to different permissions, recipient can obtain the original plaintext meshes, additional data or both. Experimental results show that the proposed method has higher embedding capacity and higher quality of the recovered meshes compared to the state-of-art methods.

In recent years, reversible data hiding in encrypted images (RDHEI) that embeds additional data into the encrypted image content has received more and more attention. In previous RDHEI methods, there is no one considering the correlation between neighboring pixels. In this paper, to better explore the correlation between neighbor pixels, a novel reversible data hiding method in encrypted images with two-MSB (MSB and second MSB) prediction is proposed. After analyzing the original image content and detecting all the possible prediction errors, we encrypt the original image content using the bitwise exclusive-or (XOR) operation and highlight prediction error based on the error location binary map. Finally, all available pixels are embedded with additional data by two-MSB substitution. In our method, reversibility, separability and error-free data extraction are realized. The experimental results show that the proposed method providing a higher embedding rate and better quality of directly decrypted image compared with other start-of-the-art methods.

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.

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.

Data hiding and encryption are the two successful techniques to protect the information in public domain while transmission. Conceal information in a cover image and reconstruction of the same cover image after extracting the hidden information without any alteration is recognized as reversible data hiding (RDH) technology. Reversible data hiding is mainly found application in military and medical field applications. Many such types of schemes are technologically advanced to ensure the security, genuineness, and integrity of the images on transmission through Internet or through any other medium. The cover image used here is a gray image and it is preprocessed for prediction error detection. After the detection of possible prediction error pixels, the position of the predicted error pixel is stored in a binary location map. For prediction error detection the median edge detector (MED) is used. By using information in the binary location map, the error position information is inserted to the encrypted image by most significant bit (MSB) substitution method. Chaotic generator used in this work for encryption process is two chaotic logistic map, which is used to produce pseudo-random binary sequence. The encryption algorithm used here is Coupled Chaotic Logistic Map, to generate pseudo-random binary sequence to encrypt the image pixel by pixel. The secret message is embedded into the prediction error highlighted encrypted image by MSB substitution method. MSB prediction method is used in the decoding phase as it is essential for the successful reconstruction of cover image. The embedded image can be productively extracted and the original cover image can absolutely recovered and its PSNR and SSIM value are infinity and 1.00, respectively. By using the coupled logistic chaotic map, high visual security, better NPCR, UACI, and correlation values are achieved.

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.

This article proposes an effective way of implementing a multiply accumulate circuit (MAC) for high-speed floating point arithmetic operations. The real-world applications related to digital signal processing and the like demand high-performance computation with greater accuracy. In general, digital signals are represented as a sequence of signed/unsigned fixed/floating point numbers. The final result of a MAC operation can be computed by feeding the mantissa of the previous MAC result as one of the partial products to a Wallace tree multiplier or Braun multiplier. Thus, the separate accumulation circuit can be avoided by keeping the circuit depth still within the bounds of the Wallace tree multiplier, namely O ( log 2 n ), or Braun multiplier, namely O ( n ). In this article, three kinds of floating point MACs are proposed. The experimental results show 48.54% of improvement in worst path delay achieved by the proposed floating point MAC using a radix-2 Wallace structure compared with a conventional floating point MAC without a pipeline using a 45nm technology library. The same proposed design gives 39.92% of improvement in worst path delay without a pipeline using a radix-4 Braun structure as compared with a conventional design. In this article, a radix-32 Q 32.32 -format-based floating point MAC is proposed using a Wallace tree/Braun multiplier. Also this article discusses the msb prediction problem and its solution in floating point arithmetic that is not available in modern fused multiply-add designs. The performance results show comparisons between the proposed floating point MAC with various floating point MAC designs for radix-2,-4,-8, and -16. The proposed design has lesser depth than a conventional floating point MAC as well as a lower area requirement than other ways of floating point MAC implementation, both with/without a pipeline.