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.

Electronic records of a patient’s health history are often shared among healthcare providers, and patient data must be kept secure to maintain the privacy of patients. One way of doing this is through data hiding, and this paper demonstrates a scheme to achieve this. This paper proposes a capacity-raising reversible data-hiding scheme using an empirical rules table in dual images. The aim of this research is to avoid drawing awareness to the transmission of information by providing a steganographic technique capable of embedding high-capacity data into an image while maintaining the good quality of the image. To hide the secret message(s), a rules table containing 13 entries is presented. This rules table is extendable to a table of up to 262,133 entries (with each entry containing one distinct character) that are related to the 13 entries in terms of the rules. The rules of this table are used during the embedding and extraction procedures. In the proposed method, 512 × 512 images are divided into 1 × 2 blocks where adjacent pixels are represented using x and y for both embedding and extraction, respectively. Recovery of the cover image from the stego image is also achievable during the extraction process. Conducted experiments show that the proposed method has an average pixel-to-signal noise ratio of 52.65 dB, which is higher than that achieved with the methods discussed in this paper. Additionally, the proposed method can embed a wider range of characters (depending on the image size) as compared to the rest of the methods, hence its high embedding capacity of 4.25 bpp. The proposed method can also withstand security attacks such as RS, pixel value difference, entropy, and chi-square attacks. The proposed method is also undetectable under visual attack analyses such as the difference histogram, pixel difference histogram, and visual inspection. Based on the higher embedding capacity, pixel-to-signal noise ratio, the ability of this method to be undetected under visual attack analysis, and the ability of this method to withstand security attacks, it can be concluded that the proposed method is superior to the other methods.

The whole world is quickly transforming into an information world with the setup of smart cities, among other things. Information and other forms of privacy are therefore at risk due to the growing intelligence of hackers. Therefore, to enhance the security of information, a capacity-raising interpolation method based on histogram shifting is proposed. According to the experimental results, the capacity-raising interpolation method based on histogram shifting produces high-quality images with a significantly high embedding capacity, outperforming other methods. Apart from the already-mentioned advantages, the proposed method is reversible and can recover images in a lossless manner.