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The rise of online sharing platforms has provided people with diverse and convenient ways to share images. However, a substantial amount of sensitive user information is contained within these images, which can be easily captured by malicious neural networks. To ensure the secure utilization of authorized protected data, reversible adversarial attack techniques have emerged. Existing algorithms for generating adversarial examples do not strike a good balance between visibility and attack capability. Additionally, the network oscillations generated during the training process affect the quality of the final examples. To address these shortcomings, we propose a novel reversible adversarial network based on generative adversarial networks (RA-RevGAN). In this paper, the generator is used for noise generation to map features into perturbations of the image, while the region selection module confines these perturbations to specific areas that significantly affect classification. Furthermore, a robust attack mechanism is integrated into the discriminator to stabilize the network’s training by optimizing convergence speed and minimizing time cost. Extensive experiments have demonstrated that the proposed method ensures a high image generation rate, excellent attack capability, and superior visual quality while maintaining high classification accuracy in image restoration. [ABSTRACT FROM AUTHOR]

In recent years, there has been an increasing concern regarding the security and copyright issues associated with images. Unscrupulous individuals exploit electronic images through theft and manipulation, subsequently disseminating them widely, thereby posing significant threats to image copyright ownership and reliability. To address potential screen-shooting attacks on images, this paper proposes a robust watermarking algorithm based on entropy-weighted Harris corner detection and adaptive embedding radius. Firstly, this algorithm uses entropy as the weighted coefficient of Harris corner response values to extract feature points with rich texture features and high robustness. Then, the SIFT algorithm is used to assign orientations to feature points and construct and filter out non-overlapping feature regions. Next, the embedding radius of the watermark is adaptively selected based on the average gray value of the image feature region, and the watermark is embedded into the DFT coefficients of the image feature region. Finally, after completing the watermark embedding in all feature regions, the watermarked image is obtained. In the watermark extraction stage, the captured image is first geometrically distorted and then processed with a Gaussian function before extracting the watermark information from the image. Experimental results show that this algorithm has strong robustness against screen-shooting attacks and common image attacks, while maintaining high transparency. [ABSTRACT FROM AUTHOR]

Detection of double Joint photographic experts group (JPEG) compression is a major part of image forensics, especially double JPEG compression detection with the same quantization matrix is still a challenging problem. Detection of double JPEG compression for different quantization matrices has achieved good performance so far, and some methods for detecting the same quantization matrix have been proposed. However, most methods designed for grayscale images, where they utilize only truncation and rounding errors, not fully exploiting all the useful information of color JPEG images. In addition, there is no suitable model to analyze the convergence of JPEG images. These results in poor accuracy of the double compression detection for color JPEG images with the same quantization matrix. To solve this problem, we propose an effective method that utilizes third-order polynomial fitting for error convergence curves. Firstly, five successive compressions are used to extract the quantization error, dequantization error, coefficient error, and truncation error in each compression and decompression process. Secondly, based on the convergence characteristics of these four types of error information, a third-order polynomial model and least squares are applied for the fit, and then, the slope of each point of the fitted curve and the difference of the slopes are used as convergence characteristics. Moreover, the fitted curves predict the pre-compression state, which can effectively amplify the gap between single and double compression. Finally, support vector machines (SVM) are used to train and predict the final features. The experiments illustrate that the proposed method enhances accuracy by 2–3% compared to the most recent method and by approximately 15% compared to the earlier method in multiple datasets, including NRCS, MIXDATA, and MIXDATA-I. [ABSTRACT FROM AUTHOR]

The traditional image encryption method is to encrypt the plain image (PLI) into a noise-like encrypted image (EI), which can hide the information of the PLI well. However, when the EI is transmitted over the Internet, it is easy to attract the attention of hackers due to its special appearance, and the probability of EI being attacked is also greatly improved. To solve this problem, a visually secure image encryption scheme (VSIES) is proposed in this paper by using the newly designed one-dimensional sinusoidal chaotic (1-DSC) map, P-tensor product compressive sensing and discrete U transform (DUT). First, a key generation mechanism is designed where the secure hash algorithm SHA-512 is used to generate the key parameters. Then, this key is used to control the 1-DSC map to generate a measurement matrix, and the sparse coefficient matrix of the PLI is measured. Next, a double zigzag confusion method is designed to scramble the measurement values and the obtained image is diffused to find the secret image (SE). Finally, in order to randomly embed SE into a carrier image to obtain a cipher image with visually meaningful, a DUT-based embedding technique is proposed. The experimental results show that the information entropy value of the SE generated by the encryption scheme is close to 8, which proves that our encryption scheme has a good encryption effect. The visual security (VIS) of our encrypted images is 10–15 dB higher than some existing VSIES, which fully proves that our proposed encryption scheme has high VIS. [ABSTRACT FROM AUTHOR]

Advances in mobile communication have enabled images to be shared more conveniently, and the consequent risk of privacy breaches has been increasingly emphasized. Previously, traditional image encryption algorithms were mostly adopted by individuals to encrypt plain images into noise-like meaningless cipher images. This type of algorithm provides security for image privacy protection but is unable to achieve usability in cloud platforms. Furthermore, existing image encryption algorithms only target the protection of lossless compression or non-compressed formats images (e.g., BMP, PNG, etc.), but neglect the encryption needs of JPEG format images. Since the latter has the benefits of less file storage and excellent visual quality, it has been widely applied in a variety of scenarios. Thus, a thumbnail preserving encryption (TPE) scheme based on Markov model (TPE-MM) for JPEG images is proposed to equilibrate security and availability. Specifically, an approximate sum-preserving encryption method (ASP-EM) in restricted range based on its features is proposed to preserve the plain thumbnail features to accomplish cipher image usability. Subsequently, an adaptive encryption method based on Markov model (AEM-MM) was proposed to improve the encryption effect of cipher images and retain the compression performance of JPEG images. Simulation experiments show that the cipher image has good visual quality, low expansion rate, and is resistant to outline attacks. [ABSTRACT FROM AUTHOR]

Chaotic systems have played a vital role within the domain of chaos-based image encryption, owing to its significant advantages including sensitivity to initial values, ergodicity and others. Nonetheless, the current low-dimensional and less-scroll chaotic systems exhibit low complexity and randomness, leading to unsatisfactory security performance of the associated image encryption schemes. To settle the aforementioned issue, this paper introduces a novel hyperchaotic system with five scrolls and explores its application in visually meaningful image encryption (VMIE). Firstly, a new 5-scroll Rossler hyperchaotic system (5-SRHS) is designed building upon the principle of translation transformation (PTT), using the Rossler chaotic system (RCS) as a foundation. The performance of the 5-SRHS is extensively analyzed using various techniques, including but not limited to phase diagrams, Lyapunov exponents, and the NIST test. Subsequently, based on the 5-SRHS, a VMIE method is introduced. Specifically, to improve image reconstruction quality and reasonable allocation of sampling resources, a sub-region adaptive block compressive sensing (SR-ABCS) driven by image texture features is presented and applied to pre-encrypt the plain image, resulting in the generation of the encrypted image. Next, the obtained encrypted image is dynamically embedded into the host image utilizing improved grayscale difference statistics (IGDS) and 2K correction, enhancing imperceptibility of the steganographic image. Moreover, SHA-256 is integrated with the 5-SRHS to generate plaintext-related random sequences, further achieving higher security. Simulation experiments validate that the proposed scheme surpasses existing state-of-the-art (SOTA) schemes regarding steganography and reconstruction quality. Moreover, it is proven not only for secure transmission of natural images but also for medical images. [ABSTRACT FROM AUTHOR]

Magnetic resonance (MR) angiography is one of the main diagnostic approaches for cardiac-cerebral vascular diseases. Nevertheless, the non-contrast-enhanced MR angiography suffers from its intrinsic problems derived from the blood flow-dependency, while the clinical Gd-chelating contrast agents are limited by their rapid vascular extravasation. Herein, we report a hypersensitive MR angiography strategy based on interlocking stratagem of zwitterionic Gd-chelate contrast agents (PAA-Gd). The longitudinal molar relaxivity of PAA-Gd was 4.6-times higher than that of individual Gd-chelates as well as appropriate blood half-life (73.8 min) and low immunogenicity, enabling sophisticated micro-vessels angiography with a resolution at the order of hundred micrometers. A series of animal models of cardiac-cerebrovascular diseases have been built for imaging studies on a 7.0 T MRI scanner, while the clinical translation potential of PAA-Gd has been evaluated on swine on a 3.0 T clinical MRI scanner. The current studies offer a promising strategy for precise diagnosis of vascular diseases. Current contrast-enhanced magnetic resonance angiography approaches are sub-optimal. Here the authors present a hypersensitive MR angiography strategy based on interlocking stratagem of zwitterionic Gd-chelate contrast agents (PAA-Gd), enabling sophisticated micro-vessel angiography of cardiac-cerebrovascular diseases with ultrahigh resolution. [ABSTRACT FROM AUTHOR]

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The cost of collecting and labeling open-sourced datasets which promote the development of deep learning is expensive. Thus, it is important to design an efficient open-sourced data set protection algorithm to detect the open-sourced data sets used in illegal ways. In this paper, a protection algorithm based on adaptive robust blind-watermark is proposed suitable for multiple paired open-sourced datasets, and the evaluation criteria of the algorithm are defined. Specifically, in the embed stage, the highly concealed of the watermark is realized by combining UNet and double GAN to take into account the local and global features of the carrier and the watermark image. A preprocess network is used in the Embedding network to adapt different watermark size. In the extraction part, a modified feature sharing UNet with GAN is used to ensure robustness of the extraction network. Paired datasets are used for training to ensure accurate extraction of watermarks. After the target model is trained using the watermarked dataset, its inference output will contain watermark information. When it is believed that a suspicious model is illegally trained with the dataset, it can be verified by the watermark extracted from inference output of the suspicious model. We evaluate our method on three target models including nine datasets. The results show that our framework successfully verifies the dataset used illegally and without a noticeable impact on the target model task when training with the watermark dataset. [ABSTRACT FROM AUTHOR]

Deep neural networks (DNNs) are prone to produce incorrect prediction results under the attack of adversarial samples. To cope with this problem, some defense methods are presented. However, most of them are based on adversarial training, which has great computational consumption and does not start from strengthening the architecture of the network model itself to resist the adversarial attack. Recent studies have shown that feature denoising can remove the adversarial perturbations in the adversarial samples. In this paper, we propose a lightweight denoising network with residual connection (LDN-RC), on which the internal denoising block and the intermediate denoising block are introduced for feature denoising and sample denoising, respectively; the two denoising blocks are combined in the network model, which can withstand the interference of the adversarial perturbations in the adversarial samples to a large extent and also save computational resources. In the training strategy, a two-stage denoising approach and fine-tuning are presented to train the RESNET network model on MNIST, CIFAR-10, and SVHN datasets, and the accuracy of the enhanced network model exceeds 60% on all three datasets under the -PGD white-box attack, which demonstrate that LDN-RC can effectively improve the adversarial robustness of the network model. [ABSTRACT FROM AUTHOR]

With the development of cloud storage, more and more users upload images to the cloud. However, images stored in the cloud face the risk of unauthorized data mining by cloud service providers and being stolen by hackers. Encryption can protect image privacy, but traditional image encryption algorithms sacrifice image usability for security. To protect privacy while preserving image usability, two approximate thumbnail-preserving encryption (TPE) schemes, called dynamic range preserving encryption (DRPE) and approximate TPE with LSB Embedding (TPE-LSB), have been presented by Marohn in 2017. However, there is the possibility of decryption failure for DRPE, the cipher image robustness is poor for TPE-LSB, which cannot resist noise attacks. Additionally, both methods have the problems of the high file expansion rate of cipher image and poor perceptual quality of cipher image thumbnail. To solve these problems, a multi-level DWT information self-embedding method for thumbnail preserving encryption (TPE-ISE) is proposed. Compared with the previous works, the TPE-ISE scheme achieves a controllable compression ratio of cipher images, the perceptual quality of cipher images is closer to that of plain images, and the ability of cipher images to resist noise attacks is stronger. A series of experiments verify the superiority of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Encryption of meaningful images into unidentifiable noise-like images can improve the security of images during storage and transmission. In this paper, a novel color image encryption method based on the lifting scheme and cross-component permutation (CIE-LSCP) is introduced. First, original image is divided into red, green and blue components, and then the three components are processed by a preprocessing strategy based on the lifting scheme (PSLS) to change the statistical distribution of the pixels. Second, a block-based cross-component permutation based on index vectors (BCPIV) is presented to divide three preprocessed components into blocks and perform the cross-component permutation operation on them, and three random matrices are utilized to determine the target component, target block and target pixel position of the current pixel to be moved, respectively. Subsequently, a multi stochastic diffusion based on random sequences (MSDRS) is developed to alter the pixel values of the permutated components, and finally a ciphertext image is gotten by merging the three components. Moreover, the SHA256 hash values of the plaintext image are used to obtain the initial parameters of the chaotic system, and the obtained chaotic sequences are applied in the image encryption process. Wherein the generated random sequences are highly reliant on the plaintext image, making the encryption scheme resistant to both known-plaintext attacks and chosen-plaintext attacks. Experimental results demonstrate that the proposed scheme has good security and effectiveness and can be applied for secure transmission of digital images over the Internet. [ABSTRACT FROM AUTHOR]

Recently, most histogram shifting-based reversible data hiding (RDH) algorithms have considered the impact of textural information on embedding performance, while exploiting pixels with different local complexities. Prioritizing pixels with small local complexities to accommodate secret data decreases the invalid shifting pixels, thereby reducing distortion. However, though effective, the local complexity is not calculated precisely enough, which results in inaccurate texture division and does not considerably reduce distortion. Thus, we employ a novel local complexity calculation and multipeak embedding (MPE) to effectively improve the capacity-distortion performance. Specifically, the host image is first preprocessed by the dot-cross pattern and divided into two subsets. Then the pixel local complexity of each subset is computed by using the spatial correlation of pixels (SCOP) to improve calculation accuracy. Finally, the peak bins to be expanded in the regions with lower local complexity are adaptively selected for embedding with secret data by MPE. To ensure that the authorized operator can securely gain error-free secret data, we design the location index sequences as special keys, which guarantee the algorithm reversibility and enhance the security of the algorithm at the same time. Experimental results show that our algorithm has superior embedding effectiveness compared to some state-of-the-art RDH methods. [ABSTRACT FROM AUTHOR]

With the advancement of multimedia technology and coming of big data era, the size of image data is significantly increased. However, the traditional image encryption methods cannot solve the emerging problems of efficient compression. To settle with this challenge, an effective content-adaptive image compression and encryption method based on compressive sensing and double random phase encoding (DRPE) is proposed in this paper. The original image is converted to one low-frequency part and three high-frequency parts by DWT and then permutated by sorting-based chaotic sequences. Afterward, a novel measurement matrix optimization algorithm based on adaptive step size is presented to measure the high-frequency components. To enhance the security of the scheme, the DRPE, quantization, and diffusion are successively performed on the complex matrix composed of the shuffled low-frequency component and three measurement value matrices to obtain the cipher image. Logistic-Sine chaotic system is utilized to produce the chaotic keystreams for the encryption process, and its system parameter and initial value are determined by the information entropy of the plain image and external key parameters, so that the proposed cipher can withstand known-plaintext and chosen-plaintext attacks effectively. Numerical experiments demonstrate the effectiveness of the proposed image compression and encryption algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new image compression and encryption scheme (ICES) based on compressed sensing (CS) and double random phase encoding (DRPE), as well as a joint decryption on the cloud and user side. In the encryption, the plain image is firstly decomposed into approximate component and detail components by discrete wavelet transform (DWT), then the approximate component is scrambled, and detail components are compressed using a measurement matrix constructed by the Logistic-tent system. Secondly, the scrambled approximate component and compressed detail components are combined into a complex matrix, and then it is subjected to DRPE to get the amplitude and phase matrices. Subsequently, the resulting matrices are performed random pixel scrambling and diffusion to obtain the final cipher image. During the decryption, the cipher image is first partially decrypted on the cloud, and then fully decrypted to recover the original image on the user side, and we can judge whether the cloud has cheated us by comparing the contour similarity between the approximate component and the detail component returned by the cloud to the user, which not only significantly shortens the decryption time, but also effectively prevents malicious deception of the cloud. Experimental results and performance analyses demonstrate its effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

Visually meaningful image encryption may keep the data security and appearance security of the digital images. However, there are still security and efficiency shortcomings existing in the current algorithms. To solve these problems, we propose an effective visually meaningful color image encryption scheme by combining hybrid multi-objective particle swarm optimization (HMPSO), block compressed sensing (BCS) and Hessenberg decomposition (HD). Firstly, the R, G, B components of color image are segmented averagely and represented sparsely by discrete cosine transform (DCT), respectively. Next, the obtained sparse images are scrambled by the use of zigzag path and measured by BCS to obtain the measurement value matrices. To improve its security, the key associated with the plain image is used as the initial value of the nonlinear chaotic system Henon, and a cross-component dislocation and diffusion strategy are applied to the measurements using the chaotic sequences generated by Henon to obtain the secret image, which enhances the ability of the algorithm to resist chosen-plaintext attack. Subsequently, the secret images are fused into the carrier image by the HD embedding algorithm to generate the final visually meaningful cipher image. In addition, in order to enhance the quality of the reconstructed image and cipher image, HMPSO is implemented to optimize the threshold value of sparse coefficient modification and the embedding rate simultaneously. Simulation results and performance analysis demonstrate the effectiveness, confidentiality and robustness of the proposed scheme. [ABSTRACT FROM AUTHOR]

In this paper, an image cipher is presented based on DNA sequence operations, image filtering and memrisitve chaotic system. Firstly, plain image is preprocessed by a self-updating transformation based on dynamic image filtering (STDIF), which may solve the problem that conventional filtering is invalid for special image such as all-zeros. Subsequently, the resulting image is converted into the DNA sequences by the dynamic DNA encoding rules, and the rules are produced by plain image information and chaotic system. Next, the DNA matrix is permutated by a double random 3D matrix scrambling (DR3DMS), thus every element may arbitrarily move to other position. Thereafter, the permutated matrix is diffused by a plane diffusion of 3D DNA matrix controlled by plain image information (PD3DPI) to resist statistical attacks. Finally, the obtained DNA matrix is transformed into cipher image via DNA decoding rules. Additionally, SHA 256 hash function value of plain image is applied to choose keystreams from the obtained chaotic sequences, which not only solves the problem of repeatedly generating chaotic sequences when encrypting different images, but also results into higher difficulty for hackers to decipher the method by use of plaintext attack. Experimental results and security analyses demonstrate its security and effectiveness. [ABSTRACT FROM AUTHOR]

Compared to 1D compressed sensing (CS), 2D CS is more efficient for compressing the plaintext image from two directions, but security level of current 2D CS-based ciphers is unsatisfactory. To solve this problem, this paper presents a novel color image compression and encryption algorithm by combining 2D CS, information entropy and chaos. Firstly, the color image is decomposed into red, green and blue components, then they are sparsely transformed by the discrete wavelet transform (DWT) to get three sparse matrices. Next, the obtained matrices are observed by two asymptotical deterministic random measurement matrices based on information entropy and counter (ADMMIC), which not only encrypts the plaintext image, but also compresses it in proportion to reduce the transmission bandwidth and storage space. Subsequently, the corresponding measurement value matrices are shuffled by a double random scrambling based on Arnold map and index vector (DRSAIV) to eliminate the correlation between adjacent pixels. Furthermore, the obtained permutated matrices are diffused by a simultaneous multiple random diffusion of inter–intra components (SMRDIC) to obtain the final cipher image, the plaintext pixel to be diffused, the key matrix involved in diffusion and the position of the obtained ciphertext pixel are all unpredictable, which makes statistical attack invalid. In addition, information entropy values of plaintext image are obtained to generate the initial values of the used chaotic systems, which greatly improve the ability to resist the known-plaintext and chosen-plaintext attacks. Simulation results and security analyses verify that this algorithm has good compression and high security. [ABSTRACT FROM AUTHOR]

In this paper, an effective image encryption algorithm based on 3D Latin cube and memristive hyperchaotic system is proposed. The architecture of preprocessing, permutation and diffusion is utilized. The original image is updated for the first time by the preprocessing process to modify statistical distribution of image pixels, which includes random data embedding and alphabetic XOR operation (AXO). Subsequently, the resulting image is converted to a 3D bit matrix, permutation based on 3D Latin cube (P3DL) and diffusion based on 3D Latin cube (D3DL) are successively manipulated on it to obtain the final cipher image, such that each bit element of plain image may move to any position across the bit plane, and the general transformation of matrix dimensions from permutation to diffusion is also unnecessary. Additionally, the adoption of preprocessing operation makes the permutation easy to resist attacks against special images. Moreover, random data used in preprocessing and 3D Latin cubes utilized in P3DL and D3DL are controlled by a 4D memristive hyperchaotic system, its initial values are computed by information entropy of plain image, which makes the chosen-plaintext and known-plaintext attacks invulnerable. Simulation results and performance analyses verify the effectiveness and security of the proposed image encryption scheme. [ABSTRACT FROM AUTHOR]

At present, information entropies of cipher images gotten by some CS-based image cryptosystems are lower than 7, which make them vulnerable to entropy attack. To cope with this problem, we propose a novel image compression–encryption method based on compressive sensing (CS) and game of life (GOL). Encryption architecture of permutation, compression and diffusion is utilized. Firstly, a plaintext-dependent game-of-life-based scrambling method is presented to shuffle the sparse coefficient matrix of plain image, and the permutation matrix is constructed by rules of GOL, which may effectively reduce the adjacent pixel correlation and enhance the scrambling effect. Secondly, the confused matrix is compressed by CS and diffused using a key matrix to get the cipher image. Additionally, a five-dimensional (5D) memristive hyperchaotic system is used to generate chaotic sequences. They are utilized to construct measurement matrix, to generate initial cell matrix of GOL and to produce key matrix. Information entropy of plain image and external key parameters are combined to compute initial values of the hyperchaotic system. Therefore, our algorithm has high sensitivity to original image and it may resist against known-plaintext attack and chosen-plaintext attack. Experimental results and performance analyses demonstrate that the proposed encryption algorithm is effective to withstand various typical attacks, and it may be applied for image secure communication. [ABSTRACT FROM AUTHOR]

Organic conjugated materials combining high conductivity with strong solid-state emission are highly desired for organic electronic applications, yet still rather rare. Herein, a novel luminogen (TEN) comprised by linking naphthalene diimides and tri-phenyl ethylene with vinyl bridges is reported. TEN exhibits aggregation-induced emission (AIE) behavior of a strong near-infrared fluorescence over 700 nm and the efficiency above 60.5% in the solid state, while also shows promising application in vivo bio-imaging with good permeability and extremely low background. Single crystal of TEN reveals intra- and intermolecular C-H⋯O hydrogen bonds, contributing to an inclined molecular stacking along the a-axis of the cell, creating a 1D charge carrier transporting channel under a short π-π interaction distance of 3.42 Å, which might benefit the solid emission and charge transport ability simultaneously. Solution processed bottom contact, top gate organic field effect transistors based on TEN reveal a high ambipolar charge transport ability with the hole mobility up to 0.13 cm2 V−1 s−1 and electron mobility up to 0.010 cm2 V−1 s−1. Further atomic force microscopy and X-ray diffraction analysis on TEN thin film confirm the existence of the 1D π-π stacking channel, suggesting the stacking geometry revealed in crystal crucial for facilitating high charge carrier mobility while preserving the strong solid emission at the same time. [ABSTRACT FROM AUTHOR]

Nowadays, many image cryptosystems have been cracked by chosen-plaintext attacks, for they are not highly sensitive to plain image. To solve this problem, we introduce a plaintext-related mechanism for secure color image encryption, and it is established in the generation and selection of chaotic sequences, permutation and diffusion. In the proposed image cryptosystem, the architecture of permutation and diffusion is adopted. Firstly, plaintext-related Latin-square-based block permutation is proposed to randomly shuffle pixels of the color plain image, diffusion method dependent on the plaintext and scrambled image is further given to modify pixels of permutated image, and finally cipher image is gotten. The chaotic sequence for diffusing the current pixel is dynamically generated according to the plain image and scrambled image, and diffusion operations of red, green and blue components of color plain image affect each other. Besides, chaotic sequences used in encryption are produced by new one-dimensional chaotic systems and dynamically selected, and initial values of chaotic systems are computed by plain image and external keys. Experimental results and security analyses demonstrate that our image encryption has large key space and high security level, and it can be applied for the secure communication of image information. [ABSTRACT FROM AUTHOR]

In this paper, an efficient image compression and encryption scheme combining the parameter-varying chaotic system, elementary cellular automata (ECA) and block compressive sensing (BCS) is presented. The architecture of permutation, compression and re-permutation is adopted. Firstly, the plain image is transformed by DWT, and four block matrices are gotten, and they are a low-frequency block with important information and three high-frequency blocks with less important information. Secondly, ECA is used to scramble the four sparse block matrices, which can effectively change the position of the elements in the matrices and upgrade the confusion effect of the algorithm. Thirdly, according to the importance of each block, BCS is adopted to compress and encrypt four scrambled matrices with different compression ratios. In the BCS, the measurement matrices are constructed by a parameter-varying chaotic system, and thus few parameters may produce the large measurement matrices, which may effectively reduce memory space and transmission bandwidth. Finally, the four compressed matrices are recombined into a large matrix, and the cipher image is obtained by re-scrambling it. Moreover, the initial values of the chaotic system are produced by the SHA 256 hash value of the plain image, which makes the proposed encryption algorithm highly sensitive to the original image. Experimental results and performance analyses demonstrate its good security and robustness. [ABSTRACT FROM AUTHOR]

In this paper, an image encryption algorithm based on 3-D DNA level permutation and substitution scheme is proposed. In order to improve the security level of the image encryption, a 3-D DNA level hybrid permutation scheme using chaotic sequence sorting and 3-D cat map is presented to effectively shuffle the element positions, a novel 3-D DNA level substitution method based on random number is given to directly change the elements of the 3-D DNA matrix, and dynamic and random DNA encoding rules and DNA decoding rules are designed to upgrade the randomness of the encryption results. Moreover, a 6-D hyperchaotic system is used to generate the chaotic sequence for all the encryption processes, and SHA 256 hash value of the plain image is utilized to compute the initial values of chaotic system and system parameters of the 3-D cat map. Simulation results and performance analyses demonstrate that the proposed encryption scheme has large key space, high key sensitivity and may resist against some typical attacks, and it may effectively secure the secret image information. [ABSTRACT FROM AUTHOR]

Medical image encryption may help protect medical privacy. In this paper, we propose a new medical image encryption scheme combined Latin square and chaotic system. The architecture of permutation and diffusion is adopted. Using Latin square and the plain image information, permutation based on plain image and Latin square (PPILS) is presented to shuffle the pixels of the plain image to different rows and columns, effectively weaken the strong correlations between adjacent pixels, and different images have different permutation effect. To improve the encryption effect, bi-directional adaptive diffusion is proposed to spread little change of plain images to the entire pixels of cipher images. Chaotic sequences employed in permutation and diffusion are generated from the four-dimensional memristive chaotic system, its initial values are computed by SHA 256 hash value of the plain image, and thus the proposed algorithm may withstand known-plaintext and chosen-plaintext attacks. Simulation results and performance analyses show that our image encryption scheme has good security and robustness, and it may be applied for medical image encryption applications. [ABSTRACT FROM AUTHOR]

In the paper, a novel image encryption algorithm based on DNA sequence operations and chaotic systems is proposed. The encryption architecture of permutation and diffusion is adopted. Firstly, 256-bit hash value of the plain image is gotten to calculate the initial values and system parameters of the 2D Logistic-adjusted-Sine map (2D-LASM) and a new 1D chaotic system; thus, the encryption scheme highly depends on the original image. Next, the chaotic sequences from 2D-LASM are used to produce the DNA encoding/decoding rule matrix, and the plain image is encoded into a DNA matrix according to it. Thirdly, DNA level row permutation and column permutation are performed on the DNA matrix of the original image, inter-DNA-plane permutation and intra-DNA-plane permutation can be attained simultaneously, and then, DNA XOR operation is performed on the permutated DNA matrix using a DNA key matrix, and the key matrix is produced by the combination of two 1D chaotic systems. Finally, after decoding the confused DNA matrix, the cipher image is obtained. Experimental results and security analyses demonstrate that the proposed scheme not only has good encryption effect, but also is secure enough to resist against the known attacks. [ABSTRACT FROM AUTHOR]

Image encryption is an efficient technique for image protection. This paper presents a double color image encryption (DCIE) scheme based on three-dimensional (3D) Brownian motion. The architecture of diffusion, confusion and diffusion is adopted. The proposed algorithm firstly decomposes two color plain images into R, G, B components and bit planes, then conducts XOR operation between every bit plane and a key bit plane generated from carrier images; next, arranges all the bit planes into a 3D bit matrix, performs block-in 3D Brownian motion confusion and block confusion on it, which can permute the elements across bit planes and across plain images; finally, a subsequent diffusion process is utilized to improve the encryption effect. Simulation results and performance analyses illustrate that the proposed encryption scheme can simultaneously encrypt two color images into noise-like ones that have strong ability of resisting various known attacks. [ABSTRACT FROM AUTHOR]

A novel and efficient image encryption algorithm based on the chaotic system and S-boxes is introduced in this paper, in which an original S-box is produced by linear fractional transformation (LFT) on Galois field of order 256, and then a set of S-boxes are obtained by performing zigzag confusion on the original S-box. The encryption architecture of forward substitution process (FSP) and reverse substitution process (RSP) is adopted. For each pixel of the plain image, a corresponding element in a certain S-box is chosen, and the choosing process of the S-box and element depends on two random numbers, the plain image pixel and the previous cipher pixel. Moreover, 2D-LASM is used to generate the random numbers, and its initial values and system parameter are computed by the SHA 256 hash of the plain image and the given values. Therefore, the proposed scheme has highly relationship with the original image and it can resist known-plaintext and chosen-plaintext attacks. Besides, correlated chaos and correlated substitution are used to improve the security level. Experiment results and security analyses demonstrate that the proposed image encryption algorithm is secure and efficient. [ABSTRACT FROM AUTHOR]

In the paper, a fast image encryption scheme with block permutation and block diffusion is introduced. Considering the increasing size of the image, encryption process is manipulated by block, and the encryption of every block image consists of block permutation and block diffusion. A novel plain image-related swapping block permutation strategy is presented, the swapping operation of the block image is controlled by the random chaotic sequences, and the initial value and parameter of the chaotic system are produced by SHA 256 hash value of the plain image, thus our algorithm is highly sensitive to changes of the plain image. Diffusion method within the block image (DMWBI) and diffusion method between two block images (DMBTBI) are presented to effectively eliminate the correlation of adjacent pixels in the plain image. The correlated chaos is employed to enhance the relationship of chaos, and take fully use of chaotic maps. One-dimensional Logistic-Sine System (LSS) is used to generate pseudo-random sequences during the whole encryption process. Experiment results and security analysis have proved the proposed image encryption algorithm is secure and effective. [ABSTRACT FROM AUTHOR]

In recent years, a wide variety of cryptographic algorithms based on chaos have been put forward and most of them have been proved to be successful by adopting the traditional permutation-diffusion architecture. However, one drawback these methods mostly hold is that they have little connection with the plaintext or, properly speaking, the relationship between them is rather less. The drawback makes the encryption algorithms vulnerable to the known-plaintext and chosen-plaintext attack. In addition, the secret keys are stationary at most times, and they can't be selected dynamically by the corresponding plain image pixels. In order to overcome these disadvantages mentioned above, we introduce a new chaos-based image encryption algorithm with dynamic key selection mechanisms in this paper, and present a dynamic keystream sequence group selection mechanism (DKSGSM) and a dynamic keystream selection mechanism (DKSM). They strongly enhance the relationship between the plaintext and the encryption scheme. In particular, the DKSGSM and DKSM expand the selection range of the keys and allow us to select the keys dynamically by the corresponding plaintext pixels. What's more, by adopting the bidirectional encryption, we can spread the influence to the whole image once a tiny change in plain image and this can greatly increase the security level of our encryption method. Simulation results and numerical analyses indicate that our encryption scheme is safe and efficient. [ABSTRACT FROM AUTHOR]

A novel thermosensitive block copolymer composed of poly(ethylene glycol) (PEG) and poly( N-( N-Boc-ethylenediamine)methacryloylglycylglycylamide) (PBEMAGG) with pendant amino groups was synthesized via reversible addition-fragmentation chain transfer (RAFT) polymerization. The thermosensitivity of these copolymers was studied with varying temperatures and block lengths of copolymers. The results indicated that the lowest critical solution temperatures (LCST) of this thermosensitive copolymer cover the range from 20 °C up to near 45 °C, and can be easily and precisely regulated by changing the block length or the amount of pendant amino groups. This copolymer with well-controlled LCST and pendant functional groups shows great potential for use as a smart drug-delivery system. [Figure not available: see fulltext.] [ABSTRACT FROM AUTHOR]

In situ evaluation of cell cultivation on degrading poly(ɛ-caprolactone) (PCL) films was studied. New culture surroundings were constructed for cell growth by using PCL films as substrates and adding Pseudomonas cepacia lipase to accelerate biodegradation of PCL films. MTT experiments for 10 h indicated the low cytotoxicity of lipase solution with concentration up to 0.2 mg/mL for MG-63 cells growth on PCL films. With the optimized lipase concentration and degradation time, we studied cell growth behavior on dynamically changed PCL films by adding lipase to the culture surroundings. MTT, fluorescence microscopy and scanning electron microscopy (SEM) were used to evaluate cell viability, proliferation and morphologies. It was found that cell viability and proliferation were not affected by the added lipase solution negatively. In contrast, cells cultured on degrading PCL films showed good growth behavior with clear fusiform shape and pseudopods. Importantly, the enzymatic degradation of PCL films with cells attachment showed distinctive morphology compared to the degradation in lipase solution without cells. The simultaneous cell growth and PCL film degradation were well discussed in this work, which may better understand the interaction between cell growth and polymer degradation. [ABSTRACT FROM AUTHOR]

Numerical simulation of cavitation in cryogenic fluids is important in improving the stable operation of the propulsion system in liquid-fuel rocket. It also represents a broader class of problems where the fluid is operating close to its critical point and the thermal effects of cavitation are pronounced. The present article focuses on simulating cryogenic cavitation by implementing the "full cavitation model", coupled with energy equation, in conjunction with iterative update of the real fluid properties at local temperatures. Steady state computations are then conducted on hydrofoil and ogive in liquid nitrogen and hydrogen respectively, based on which we explore the mechanism of cavitation with thermal effects. Comprehensive comparisons between the simulation results and experimental data as well as previous computations by other researchers validate the full cavitation model in cryogenic fluids. The sensitivity of cavity length to cavitation number is also examined. [ABSTRACT FROM AUTHOR]

A novel 4 K separate two-stage pulse tube cooler (PTC) was designed and tested. The cooler consists of two separate pulse tube coolers, in which the cold end of the first stage regenerator is thermally connected with the middle part of the second regenerator. Compared to the traditional coupled multi-stage pulse tube cooler, the mutual interference between stages can be significantly eliminated. The lowest refrigeration temperature obtained at the first stage pulse tube was 13.8 K. This is a new record for single stage PTC. With two compressors and two rotary valves driving mode, the separate two-stage PTC obtained a refrigeration temperature of 2.5 K at the second stage. Cooling capacities of 508 mW at 4.2 K and 15 W at 37.5 K were achieved simultaneously. A one-compressor and one-rotary valve driving mode has been proposed to further simplify the structure of separate type PTC. [ABSTRACT FROM AUTHOR]

The computation with the theory of modified Brayton Cycle indicates that higher cooling power and coefficient of performance for a pulse tube refrigerator can be achieved with He-H2 mixture as working gas than those with pure He in the temperature region of 30 K. In addition, it is found that Er3Ni, a regenerative material, is able to absorb H2 and produces Er3NiHx. The computation presents that the regenerative performance of Er3NiHx is better than that of Er3Ni due to its higher volume specific heat. Experimental results show that the pulse tube refrigeration performance in 30 K temperature region is enhanced greatly with He-H2 mixture and Er3NiHx packing. [ABSTRACT FROM AUTHOR]

Describes the characteristic of the thermoacoustically driven pulse tube refrigerator (TADPTR). Advantage of the system's application; Method used to analyzed the operation and performance of the refrigerator; Composition of the TADPTR.