A High-Capacity Reversible Watermarking Technique Using Bit-Level Expansion and Pixel Shifting

Adaptive and non-adaptive data hiding methods for grayscale images based on modulus function

A high stego-image quality steganographic scheme with reversibility and high payload using multiple embedding strategy

Reversible data hiding-based contrast enhancement can be applied to medical images, which not only allows the storage of patient information through reversible embedding, but also achieves image contrast enhancement, thereby assisting doctors in accurately diagnosing patient diseases. In response to the existing problems of mainstream methods, a novel reversible data hiding-based local contrast enhancement method for medical images is proposed. This method utilizes superpixel segmentation to segment medical images into multiple pixel blocks, and performs reversible data embedding and contrast enhancement for the pixel blocks within the region of interest (ROI). Additionally, a new embedding strategy is proposed. According to the contrast and texture features of each pixel block, histogram expansion of different degrees is carried out to effectively enhance the pixel blocks with low contrast, while avoiding excessive enhancement of the pixel blocks with high contrast. Experimental results demonstrate that, compared with the state-of-the-art mainstream methods, the proposed method not only improves the contrast in the ROI but also ensures high visual quality of the medical images.

Embedding capacity raising in reversible data hiding based on prediction of difference expansion

Embedding information in medical images is considered as one of the significant methods for safeguarding the integrity and authenticity of medical images besides providing security to electronic patient records (EPR). The conventional embedding methods deteriorate the perceptual quality of medical images making them unsuitable for proper diagnosis. To preserve the perceptual quality of medical images reversible embedding is used. The reversible embedding schemes, however, have less embedding capacity. In this work, a reversible scheme based on histogram bin shifting and RGB plane concatenation has been proposed which offers high embedding capacity as well. We have exploited the fact that medical images, unlike general images, consist of a large number of peaks and zero points that can be employed for reversibly embedding the data. Reversibility ensures that original image restoration takes place after the extraction of embedded data, which is of great importance in medical images for proper diagnosis and treatment. We have used various subjective and objective image quality metrics for analyzing the scheme. The proposed scheme has been shown to provide a Peak Signal to Noise Ratio (PSNR) value of above 56 dB for an embedding capacity of 0.58 bits per pixel (bpp). The results obtained show that the performance of scheme presented is far better in comparison to the state-of-the-art.

Data hiding algorithms can achieve the issue of information security when secret data are transmitted via the public network. This paper proposes a novel data-hiding scheme based on pixel value differencing and pixel shifting to increase embedding capacity and visual quality. In the proposed method, the cover image is first divided into nonoverlapping blocks, and eight groups of different values are generated with the center pixel as the reference pixel to embed the secret message. The pixel shifting strategy is applied to adjust the stego image to improve its quality. Experimental results show that the proposed method has an embedding capacity of 740,000 bits with a peak signal-to-noise ratio value greater than 35 dB. Therefore, it is undetected by the human eye. Other compared state-of-the-art schemes have embedding capacities of 51,219 bits, 70,217 bits, and 104,055 bits, which are lower than the proposed methods’ 740,000 bits. The RS, chi-square, and rotation attack analyses prove that the proposed method can withstand security attacks. Thus, the proposed method performs better than other state-of-the-art methods with respect to embedding capacity and ability to withstand attacks.

The reversible data embedding is emerging due to its various watermarking and steganography applications. The requirement of reversibility may lead to more modifications to the cover content which result in the trade off between the visual quality and embedding capacity. In this paper we propose a reversible data embedding scheme for MPEG-4 video, striking the trade off, which embeds the data into non-zero AC coefficients of quantized DCT blocks. The experimental results show that the proposed scheme improves both the visual quality and embedding capacity.

Reversible watermarking methods have drawn attention of many researchers in recent years because original cover objects can be completely restored upon extraction of embedded information. The prediction error expansion (PEE) embedding proposed by Thodi and Rodriguez can embed one information bit into one cover pixel and achieve good visual quality of watermarked images. However, the PEE method is not a generalised scheme and its embedding capacity measured by bit per pixel (bpp) and visual quality measured by peak signal-to-noise ratio (PSNR) can be improved. Thus, we propose two novel schemes based on the PEE method by using pixel partition strategies to improve embedding capacity and/or visual quality. The first proposed scheme makes the PEE method be generalised and the second proposed scheme can embed more than 1 bpp. Experimental results show that the proposed schemes can significantly improve visual quality of the watermarked images produced by the PEE method when embedding capacity falls within the range [0·1, 1]. In particular, when an embedding capacity belongs to the range [0·1, 0·5], in average, the first proposed scheme with K = 1 can improve the PSNR of the PEE method at least 13 dB for test images. In addition, when embedding capacity falls within the range [0·1, 1], in average, the second proposed scheme with K = 1 can improve the PSNR of the PEE method at least 14 dB for test images.

4D chaotic system-based secure data hiding method to improve robustness and embedding capacity of videos

This work presents a novel reversible data hiding scheme based on combinations of pixel orientations located at two steganographic images to enhance embedding capacity and preserve good visual quality. Before secret data are embedded, the proposed scheme converts the data into a sequence of digits in a base-5 numeral system. The conversion then extends the abilitity to carry more secret data. When the secret data embedding procedure is performed, the original cover pixel value can only be modified by at most plus or minus one, thus ensuring that the stegano-image also has excellent visual quality. Moreover, image recovery does not require overhead information. Experimental results demonstrate that the embedding capacity is around 1.07 bpp and PSNR reaches 49.6 dB. The experimental comparison also reveals that the proposed scheme outperforms other related schemes in terms of embedding rate and retains a high visual effect of stegano-image.

Information Technology is continuously making communication much easier thereby drawing the interest of millions of users, including medics, to data communications. However, security of the information communicated still remains issues of concern, especially when it comes to patients’ confidential information. Apparently, various concepts have being proposed to solving most of the problems of information security, such as the cryptography and the steganography. Image steganography approach focuses on concealing the existence of information from unintended person. Least Significant Bit (LSB) approach of hiding data is one of the most popular in this regards but with weakness of low embedding capacity and therefore low security. Consequently, there have been several attempts by researchers to improving the embedding capacity and low security in LSB. This study therefore proposes hardware-accelerated steganography data hiding framework towards addressing the weaknesses of low security and embedding capacity exhibited in LSB data hiding approach. Within Compute Unified Device Architecture (CUDA), the proposed framework was able to conceal secret data using the LSB approach where the pixels of the cover image and the secret data were converted into their equivalent binary bits, and the binary bits grouped into bytes of 8-bits each. The LSB of the cover image was replaced with the bits of the secret data starting with the most significant bit of each byte of 8-bit of the secret data, until the whole data is fully embedded in the cover image to generate the stego-image. The proposed framework was further evaluated for possible security of the embedded secret data by encrypting the stego-image with password. The experimental results show that the images in PNG, JPG and JPEG format tend to embed and hide the secret data successfully but with increase in the size of the generated stego-image, while images in TIFF and BMP format tend to embed and hide the secret data successfully and retain their original sizes. Interestingly, the entire data hiding stages were achieved within 3s for up to 110KB of data and not more than 4s for 192KB.

A novel data hiding scheme based on modulus function

Cloud computing is an Internet-based computing model that shares computing resources such as computers, servers, and storage. In future smart cities, new applications can take advantage of cloud computing; for example, a cloud-based home health-care system can provide immediate disease management by analyzing medical images. However, if the size of cloud data is large (e.g., medical images), their transition through the Internet is time consuming. Cloud data authentication is another problem that should be addressed. To address the aforementioned problems, this study presents a novel data hiding method based on the block truncation coding (BTC) image compression technique. This method has two advantages: reduces image size and increases security. This study also proposes a block classification scheme for determining smooth blocks, complex_1 blocks, and complex_2 blocks in an image. Secret data are embedded in these three block types using different approaches. To improve the quality of images without damaging the secret data, we propose a progressive data hiding strategy and integrating an iteration-based halftoning method into BTC. When decoding, the secret data are extracted without recalling the original image. According to experimental results, the proposed method outperforms existing methods in both embedding capacity and image quality evaluations.

Data embedding is a technique for delivering secret data over Internet. Digital images are widely used cover media for carrying secret data. This is because the distortion of images is hard to distinguish by human eyes. Because of the image property, data embedding method embeds as many secret data as possible. This paper presents a high payload data embedding technique by employing the concepts of irreversible data embedding and reversible data embedding. Chang et al.'s embedding method and Tian's embedding method are two key embedding operations used in the proposed method. The proposed method embeds secret data twice. First, secret data is embedded by using Chang et al.'s method. Then, Tian's method is applied to embed the secret data. The experimental results show that the proposed method embeds 2.49 secret bits into one pixel with higher than 39 dB visual quality of stego image.

Data hiding for digital images is referred to as an approach of embedding confidential or sensitive information into a cover image. Besides embedding capacity and visual quality, computational complexity is the most important criterion to evaluate the performance of a data hiding method. At present the turtle shell matrix is used extensively in data hiding; unfortunately, most of the turtle shell-based data hiding methods are still time consuming. In this paper, we proposed two enhanced real-time turtle shell-based data hiding schemes. One applies the original turtle shell matrix to guide data embedding, achieving an embedding rate of 1.5 bpp; while the other slightly modifies the structure of turtle shell matrix in such a way that each edge digit is increased by eight, resulting in an embedding rate of up to 2 bpp. The main idea of both proposed schemes is to map each cover pixel pair onto the original or modified turtle shell matrix to find out its associate set for embedding a secret digit. Then, the cover pixel pair can be modified with minimum distortion according to the associate set. Experimental results confirm that the execution time for both of the proposed schemes is much shorter than previous methods, along with better visual qualities. Therefore, the proposed schemes offer lower computational complexities to be applied to various real-time applications.