The demand for secure handling and confidentiality of information has heightened immensely in the contemporary era, particularly due to high volumes of data exchanged through the Internet. Steganography and cryptography are two widely used techniques for safeguarding data, each with its inherent strengths and limitations. Cryptography protects information by converting it into an unreadable form, guaranteeing confidentiality. However, it does not hide the fact that a communication is present, which can draw unwanted attention. Steganography conceals information within digital media to render its presence less noticeable. Nevertheless, this approach can diminish the quality of the cover media and faces challenges in achieving lossless recovery of the cover. Reversible Data Hiding in Encrypted Images (RDHEI) has been proposed to transcend these limitations, enhancing security and recoverability. RDHEI provides a robust method for extracting and embedding data while maintaining the integrity of the original image. Separable Reversible Data Hiding in Encrypted Images (SRDHEI) takes it a step further by enabling data to be decrypted and extracted separately, without requiring access to or modification of the original image. This paper presents a novel SRDHEI solution with a high embedding capacity of 0.691 bits per pixel (bpp), which is achieved by combining Wang’s “multiple-bit RDH scheme without histogram shifting” with additive homomorphic encryption concepts. Experimental comparisons demonstrate that the new solution outperforms other methods in terms of embedding capacity, visual quality, and overall security.

Healthcare organisations are increasingly vulnerable to cyberattacks that target electronic health records (EHRs) and associated medical images, posing a threat to both patient privacy and the continuity of healthcare services. To strengthen the protection of these critical assets, this work presents a watermarking scheme that embeds patient-specific information—comprising a diagnosis report, fingerprint, and identity code—into medical images. The approach combines Integer Wavelet Transform (IWT), Singular Value Decomposition (SVD), and Principal Component Analysis (PCA) to achieve a balance between imperceptibility, robustness, and reversibility. The design was implemented on an Xilinx Zynq XC7Z020 platform, ensuring hardware efficiency while maintaining resilience against a wide range of image-related attacks. Experimental evaluation confirms that the proposed method preserves image quality and enables reliable watermark recovery, making it suitable for secure management of healthcare data. The watermarking embedding procedure experimentation was carried out using Zynq- XC7z020-CLG484I and utilises 33% of the LUTs, 574 registers, and 82 carry 4 adders. The proposed work achieves an average Peak Signal-to-Noise Ratio (PSNR) of 83 dB, a Structural Similarity Index Metric (SSIM) greater than 0.7, and a Normalised Cross-Correlation (NCC) of 1. The resultant image was intentionally subjected to 17 different attacks. The average PSNR, SSIM, and NCC between the 8-bit original watermark and the extracted watermark after attacks were 42 dB, 0.99, and 1, respectively. Eventually, the average values for the same were calculated between the 16-bit original and extracted cover after attacks were 94 dB, 0.99 and 1, respectively. These results demonstrate that the proposed work offers better imperceptibility (PSNR), robustness (NCC), and reversibility (SSIM) even after various image-related attacks.

Healthcare and telemedicine industries are relying on technology that is connected to the Internet. Digital health data are more prone to cyber attacks because of the treasure trove of personal data they possess. This necessitates protection of digital medical images and their secure transmission. In this paper, an encryption technique based on DNA mutated with Lorenz and Lü chaotic attractors is employed to generate high pseudo-random key streams. The proposed chaos-DNA cryptic system operates on the integer wavelet transform (IWT) domain and a bio-inspired crossover, mutation unit for enhancing the confusion and diffusion phase in an approximation coefficient. Finally, an XOR operation is performed with a quantised chaotic set from the developed combined attractors. The algorithm attains an average entropy of 7.9973, near-zero correlation with an NPCR of 99.642%, a UACI of 33.438%, and a keyspace of 10 203 . Further, the experimental analyses and NIST statistical test suite have been designed such that the proposed medical image encryption technique has the potency to withstand any statistical, differential, and brute force attacks.

The evergrowing virtualised information technology infrastructure is powered by cloud‐centric technology around the world. Cloud‐based multimedia storage has become an essential aspect for users and business behemoths. However, as per a survey of Norton, around 3800 breaches have been publicly disclosed with 4.1 billion numbers of records exposed in 2019, which is a 54% rise when compared to 2018. So the data security is a widely quoted barrier for cloud storage. Ciphering the confidential images before transmission and subsequent storage in cloud database needs critical attention for techno‐specific applications. In image encryption, chaos‐based keys can do better confusion, but the diffusion process using XOR is vulnerable to chosen plain text attack. The proposed colour image encryption scheme innately uses Deoxyribo Nucleic Acid coding that blends well with chaotic cryptosystem for an efficient statistical shift. The ciphered images are stored in authenticated and authorised cloud storage facilities. The experimentation is carried out with the help of Amazon Web Services storage instances. The proposed image encryption scheme offers a strong resistance towards the brute force, occlusion, statistical and differential attacks and yields near‐zero correlation and good entropy.

Medical image security relies upon the arrival of improved techniques for enhancing the confusion as well as diffusion processes in the pixel level manipulations. Non‐linear circuits constructed with hardware components can be employed for hardware–software co‐design in medical image encryption. The proposed approach has adopted Chua diode circuit for the generation of 256 × 256 random synthetic image with the entropy of 7.9972. This synthetic image has been utilised to scramble the DICOM image for the second level of diffusion as the cellular automata provides the first level of scrambling and diffusion. The average correlation coefficients of encrypted pixels are 0.00204, −0.00298 and −0.00054 in three directions. The encrypted pixels pass the NIST SP 800‐22 test suite and offer resistance to statistical, differential and chosen plain text attacks.

The utility of true random number generators (TRNGs) is not only restricted to session key generation, nonce generation, OTP generation etc. in cryptography. In the proposed work, two ring oscillator (RO) based TRNG structures adopting identical and non‐identical ring of inverters have alone been employed for confusion (scrambling) and diffusion (intensity variation) processes for encrypting the greyscale and RGB images. Cyclone IVE EP4CE115F29C7 FPGA was utilised to generate a couple of random synthetic images using the two RO architectures which took a maximum of 520 combinational units and 543 logic registers. The suggested scheme of image encryption was tested on 100 test greyscale images of size 256 × 256. This non‐chaos influenced image ciphering has resulted in an approximate average entropy of 7.99 and near‐zero correlation figures for the greyscale & RGB cipher images. The attack resistance capability was checked by performing various occlusion and noise attacks on encrypted images.

Abstract Multimedia is ruling the digital era where data storage and transmission have gained huge importance. The refuge of such data transfer has been a chief apprehension and becomes the study in the limelight, probably, forever. The universal phenomenon is to send the desired data in disguise so that only the beneficiary can avail it. In this paper, a combination of space‐filling curve with chaos has been used for encryption process. Initially, three chaotic sequences were generated using Chua's equations followed by quantification of those sequences. Key based on Hilbert curve is used for scrambling. For introducing confusion, the image is further scrambled using row and column shifting operations using the first two chaotic sequences used with space‐filling curve. Then pixel replacement has been done by bit XOR between scrambled image and the third chaotic sequence. Finally, Gould transform is applied to enhance image authentication and tamper proofing of the encrypted image. In addition, deoxyribonucleic acid‐based complementary addition rule is integrated to make the proposed scheme robust against statistical attacks, which also provides immense parallelism to generate the final encrypted image. The proposed methodology has been implemented in MATLAB 7.1. The results are compared with the existing methods. To validate the proposed system, image metrics like correlation coefficient, number of pixels change rate, unified average changing intensity, key sensitivity, cropping attacks, and noise have been computed. Copyright © 2015 John Wiley & Sons, Ltd.