• Content-adaptive video encryption in the compressed domain • Dynamically selects syntax elements based on video content complexity • Maintains full format compliance using Adaptive Syntax Integrity (ASI) • Tunable parameters balance encryption strength and bitrate increase With the ever-increasing amount of digital video content, efficient encryption is crucial to protect visual content across diverse platforms. Existing methods often incur excessive bitrate overhead due to content variability. Furthermore, since most videos are already compressed, encryption in the compressed domain is essential to avoid processing overhead and re-compression quality loss. However, achieving both format compliance and compression efficiency while ensuring that the decoded content remains unrecognizable is challenging in the compressed domain, since only limited information is available without full decoding. This paper proposes an adaptive compressed domain video encryption (ACDC) method that dynamically adjusts the encryption strategy according to content characteristics. Two tunable parameters derived from the bitstream information enable adaptation to various application requirements. An adaptive syntax integrity method is employed to produce format-compliant bitstreams without full decoding. Experimental results show that ACDC reduces bitrate overhead by 48.2% and achieves a 31-fold speedup in encryption time compared to the latest state of the art, while producing visually unrecognizable outputs.

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.

For the security risks and high transmission/storage consumption in cloud-based medical images storage systems (CMISS), reversible data hiding in encrypted images (RDHEI) provide an effective solution. Nevertheless, challenges persist concerning the security risks cause by key transmission and the large file size of encrypted medical images. Consequently, a cloud-based privacy-preserving medical images storage scheme with low consumption is proposed in this paper. First, RDHEI is applied to CMISS, where image encryption achieves privacy protection, reversible data hiding eliminates extra space consumption by index data self-hiding, and the reversibility enables lossless recovery and extraction of medical images and index data. Then, hybrid encryption is designed to achieve high security. The security of encrypted images is guaranteed by combining a one-time cryptosystem with symmetric XOR encryption, which makes our scheme can resist various attacks. Time-varying key used in XOR is encrypted by asymmetric RSA, and only public key is used in RSA, avoiding the risk of private key transmission. Finally, to reduce the file size of encrypted images and achieve low consumption, context Huffman coding is proposed to adaptively selects the block coding method by context and thresholds, and has at most 98 056 bits shorter than Huffman coding in encoded stream length. Experimental results show that the proposed scheme has better performance in terms on security, consumption, and reversibility. The minimum compression ratio in databases is 32.46%, which is 2.63% lower than the existing schemes. And the medical image and index data can be restored lossless.

Existing JPEG encryption approaches pose a security risk due to the difficulty in changing all block-feature values while considering format compatibility and file size expansion. To address these concerns, this paper introduces a novel JPEG image encryption scheme. First, the security of sketch information against chosen-plaintext attacks is improved by increasing the change rate of block-feature values. Second, a classification global permutation approach is designed to encrypt the undivided run/size, value (RSV)-based AC groups to achieve larger changes in the block-feature values. Third, to reduce file size expansion while maintaining format compatibility, the DC coefficients are rotated based on the mapped DC differences in the same category, and the nonzero AC coefficients are mapped in the same category. Extensive experiments demonstrate that the proposed algorithm is superior to existing schemes in terms of security. Notably, the average change rate of block-feature values is increased by at least 20%. Furthermore, the proposed scheme reduces the file size by an average of 2.036% compared to existing JPEG image encryption methods.

With the development of Internet of Things (IoT) and cloud services, many images generated from IoT devices are stored in the cloud, calling for efficient data encryption methods. To balance the security and usability, the thumbnail preserving encryption (TPE) has emerged. However, existing JPEG image-based TPE (JPEG-TPE) schemes face challenges in achieving low file extension, lossless decryption and better privacy protect of detailed information. To solve these challenges, we propose a novel JPEG-TPE scheme. Firstly, to achieve a smaller file size expansion and preserve the thumbnail, we reallocate the values, maintaining the sum for the DC difference instead of the DC coefficient. To ensure that the coefficients do not overflow, the valid range of reallocated difference is constrained not only by the sum but also by the neighborhood difference. Secondly, to preserve file size of AC encryption while improve the security of detailed information, the AC coefficient groups with undivided RSV are permuted adaptively. Besides, the intra TPE block swapping of DC difference, quantization table modification, non-zero AC coefficients mapping, and block permutation are used to further encrypt the image. The experimental results show that the proposed JPEG-TPE scheme achieves lossless decryption, reducing the file size expansion of encrypted images from 15.41% to 0.64% compared to the state-of-the-art scheme. Additionally, it is observed that the proposed method can effectively resist against various attacks, including the deep-learning based super-resolution attack.

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.

Reversible data hiding in encrypted images (RDHEI) technique can be used to realize privacy protection and management in the image outsourcing scenario. Most existing RDHEI schemes focus on increasing the maximum embedding rate (Max-ER), but not paying much attention to the security improvement under various attacks. In this paper, a RDHEI method based on the adaptive bit-plane (ABP) coding is proposed to improve the Max-ER. The order-index extended scrambling (OIES) encryption scheme is also developed to strengthen the RDHEI's ability of thwarting various attacks. The effectiveness of ABP coding is achieved by proper selections of the threshold. The OIES enables the design of a novel scramble-key (SK) generation method to greatly reduce the probability of generating the same SK by the same user-key. This significantly improves the ability of resisting various attacks in that the attack on the scrambling encryption is mainly via the SK rather than the user-key estimation. Analysis shows that the probability of OIES obtaining the same SK is reduced from 1.0 to 0.01 for different images and to 1/2αfor the same image. Simulation results demonstrate that the proposed ABP coding and OIES schemes outperform the state-of-the-art RDHEI algorithms in terms of the Max-ER and ability against various attacks.

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.

The reversible data hiding in encrypted images (RDH-EI) technique has been widely used to achieve privacy protection and convenient management of cloud storage images. The existing RDH-EI methods focus on the embedding capacity, reversibility, and the quality of decrypted images. This paper considers a new performance indicator of RDH-EI, the file size of encrypted images, which directly affects the cloud storage cost of content owner and network transmission efficiency. The goal is to obtain the smallest file size and to vacate sufficient space for data embedding. We propose a multi-MSB compression method that includes three strategies: the iterative MSBs-inversion prediction (IMIP), the adjacent prediction plane XOR (APPX), and the block variable length coding (BVLC). The file size of encrypted images is adaptively minimized while ensuring the format compatibility and lossless reconstruction. An encrypted image is generated by a combination of stream ciphers and bit scrambling to improve the resistance to various attacks such as the cipher-only attack (COA). Experimental results demonstrate that the proposed method has higher embedding capacity and resistance to COA compared with the current state-of-the-art methods for images with different texture complexity. The proposed algorithm can achieve the maximum embedding rate ranging from 0.74 to 4.78 bpp.