Reversible data hiding in encrypted images (RDHEI) has been recognized as an effective method for overcoming management difficulties within picture archiving and communication system (PACS). However, most existing RDHEI algorithms still encounter notable challenges when applied to the PACS, specifically in terms of their key management, embedding capacity, and security. This paper introduces a novel framework and corresponding algorithm for reversible data hiding in encrypted medical images (RDHEMI) to bridge this gap. The framework employs a unique key for each patient and maintains consistency in the key linked to patient images regardless of changes in doctor, thereby addressing key management challenges. In the proposed algorithm, Huffman tree coding (HTC) integrates Huffman coding with innovative leaf-to-leaf coding, achieving a better compression performance for medical images than move-to-front (MTF) cache and Huffman coding, as medical images contain more smooth areas. Count-encryption (CE) produces encryption keys according to the frequency of encryption occurrences for an image and ensures a peak signal-to-noise ratio under 8 dB for multiple encryptions with the same key, enhancing the algorithm’s resistance to attacks. The experimental results demonstrate that the proposed algorithm achieves high security to counter various attacks and outperforms existing algorithms in terms of the time complexity and embedding capacity, with an improvement of 0.21 bpp.

In the existing JPEG image encryption schemes , the block feature values that can be used to reduce key search space are either difficult to be changed or need to be changed through overflow processing which leads to low generality and high encryption runtime. To change block feature values without overflow processing, a novel JPEG image encryption scheme is proposed. For AC encryption, the complete and end AC groups based on undivided RSV (run/size, value) (ACG-URSV) are permuted separately to change different features. Complete ACG-URSV containing different number of RSVs is used to change the non-zero coefficients count (NCC) and energy of AC coefficients (EAC). End ACG-URSV containing the zero coefficients after position of last non-zero AC coefficient (PLZ) is mainly used to change PLZ. Besides, the intra-block RSV permutation and block permutation are used to further destroy correlation. For DC encryption, the positive DC prediction error (PDC-PE) groups modulo encryption is proposed to avoid overflow processing. The experimental results show that this paper reduces encryption runtime by more than half, improves generality by at least 20%. When quality factor of 90, the average change rates of NCC, EAC and PLZ values are increased by 96.28%, 11.68% and 29.15%, respectively.

JPEG images are widely used on the Internet. Histogram shifting reversible data hiding (RDH) methods based on quantized DCT (discrete cosine transform) coefficients are a research focus for JPEG images. Among them, frequency band selection is a key step that affects the performance of JPEG image RDH. In the existing algorithm, frequency band selection is to evaluate the embedding perform ance of the whole frequency band. But after DCT block sorting, the distribution of expand AC (alternating current) coefficients (Coefficients that can carry data) is in the front of the frequency band, so the performance evaluation of the whole frequency band will produce errors. This paper proposed an adaptive frequency band length JPEG image RDH method, which determines the used length of the frequency band while selecting the frequency band, so that can effectively reduce the invalid shift. Instead of selecting the whole frequency band length in a fixed mode for performance evaluation, the optimal combination of frequency band lengths will be selected according to the embedding performance of different lengths of each frequency band. Then, a united solution mechanism is used to solve the optimal frequency band length, and the frequency band selection is also completed while solving the frequency band length. Experimental results show that our algorithm outperforms existing state-of-the-art methods in terms of marked image visual quality and file size increment.

Image privacy protection and management face many challenges, such as privacy disclosure, copyright dispute, and traceability difficulties, with the development of big data. Reversible data hiding in encrypted images (RDHEI) has been widely considered as an effective means to tackle these challenges. In this paper, a RDHEI based on time-varying Huffman coding table (TV-HCT) method is proposed to improve the security, embedding rate (ER) and efficiency. First, the initial HCT is generated according to the prediction errors of an image, which can improve compression performance. And then, the TV-HCT is obtained by scrambling equal-length codewords in the initial HCT using timestamps. This realizes the time variability of compression coding stream (CCS) of an image in that the image TV-HCT has large change space. Analysis shows that the average change space of TV-HCT in UCID is 3.97×10327, and the average ER of three databases is more than 0.44 bpp higher than the existing algorithms. Finally, the CCS is encrypted using the designed index class scrambling method to balance complexity and security. The proposed method not only strengthens the security against brute force attack and differential attack, but also improves ER and efficiency of the RDHEI technique. Experimental results and performance analysis demonstrate that the proposed algorithm outperforms the state-of-the-art RDHEI algorithms in terms of the security, ER and complexity.

Reversible data hiding (RDH) has unique advantage in copyright and integrity protection for multimedia contents. As a typical RDH scheme, histogram shifting technique (HS) has found wide applications due to its high quality of marked image. At present, most existing HS-based RDH schemes rely on single histogram generated from cover image to hide data. Since the single histogram-based approach (SH_RDH) commonly employs smooth regions in the cover image for data hiding, it might not well utilize the cover image and exploit the correlations among image contents of different texture characteristics. In this paper, a novel RDH general framework using multiple histograms modification (MH_RDH) is proposed, which involves two key issues as follows: 1) the construction of multiple histograms based on optimized multi-features and 2) the rate allocation among multiple histograms is formulated as the one of rate-distortion optimization and solved with evolutionary algorithms. The experimental results show that the proposed method could considerably increase the payload of current MH_RDH-based embedding (ranging from 0.2 to 0.7 bpp for most test images) and outperform the other state-of-the-art SH_RDH and MH_RDH schemes.