A New Color Image Encryption Scheme Using CML and a Fractional-Order Chaotic System

The chaos-based image cryptosystems have been widely investigated in recent years to provide real-time encryption and transmission. In this paper, a novel color image encryption algorithm by using coupled-map lattices (CML) and a fractional-order chaotic system is proposed to enhance the security and robustness of the encryption algorithms with a permutation-diffusion structure. To make the encryption procedure more confusing and complex, an image division-shuffling process is put forward, where the plain-image is first divided into four sub-images, and then the position of the pixels in the whole image is shuffled. In order to generate initial conditions and parameters of two chaotic systems, a 280-bit long external secret key is employed. The key space analysis, various statistical analysis, information entropy analysis, differential analysis and key sensitivity analysis are introduced to test the security of the new image encryption algorithm. The cryptosystem speed is analyzed and tested as well. Experimental results confirm that, in comparison to other image encryption schemes, the new algorithm has higher security and is fast for practical image encryption. Moreover, an extensive tolerance analysis of some common image processing operations such as noise adding, cropping, JPEG compression, rotation, brightening and darkening, has been performed on the proposed image encryption technique. Corresponding results reveal that the proposed image encryption method has good robustness against some image processing operations and geometric attacks.     

An Effective Approach of Secured Medical Image Transmission Using Encryption Method

Various chaos-based image encryption schemes have been proposed in last few years. The proposed image encryption method uses chaotic map. The encryption is done by using 256 bit long external secret key. The initial condition for the chaotic mapping is evaluated by the use of external secret key along with the mapping function. Besides that, the proposed method is made more robust by applying multiple operations to the pixels of the image depending on the outcome of the calculation of the logistic map. Moreover, block shuffling of the image and modifying the secret key after encryption of each row is also done to add chaos to the proposed method.     

An Image Encryption Algorithm Utilizing Julia Sets and Hilbert Curves

Image encryption is an important and effective technique to protect image security. In this paper, a novel image encryption algorithm combining Julia sets and Hilbert curves is proposed. The algorithm utilizes Julia sets’ parameters to generate a random sequence as the initial keys and gets the final encryption keys by scrambling the initial keys through the Hilbert curve. The final cipher image is obtained by modulo arithmetic and diffuse operation. In this method, it needs only a few parameters for the key generation, which greatly reduces the storage space. Moreover, because of the Julia sets’ properties, such as infiniteness and chaotic characteristics, the keys have high sensitivity even to a tiny perturbation. The experimental results indicate that the algorithm has large key space, good statistical property, high sensitivity for the keys, and effective resistance to the chosen-plaintext attack.     

Adaptive medical image encryption algorithm based on multiple chaotic mapping

Digital images are now widely used in modern clinic diagnosis. The diagnostic images with confidential information related to patients’ privacy are stored and transmitted via public networks. Secured schemes to guarantee confidentiality of patients’ privacy are becoming more and more vital. This paper proposes an adaptive medical image encryption algorithm based on improved chaotic mapping in order to overcome the defects of the existing chaotic image encryption algorithm. First, the algorithm used Logistic-sine chaos mapping to scramble the plain image. Then, the scrambled image was divided into 2-by-2 sub blocks. By using the hyper-chaotic system, the sub blocks were adaptively encrypted until all the sub block encryption was completed. By analyzing the key space, the information entropy, the correlation coefficient and the plaintext sensitivity of the algorithm, experimental results show that the proposed algorithm overcomes the shortcoming of lack of diffusion in single direction encryption. It could effectively resist all kinds of attacks and has better security and robustness.     

Color image detection by biomolecular photoreceptor using bacteriorhodopsin-based complex LB films

A biomolecular photoreceptor consisting of bacteriorhodopsin (bR)-based complex Langmuir–Blodgett (LB) films was developed for color image detection. By mimicking the functions of the pigments in retina of human visual system, biomolecules with photoelectric conversion function were chosen and used as constituents for an artificial photoreceptor. bR and flavin were deposited onto the patterned (9-pixelized) ITO glass by LB technique. A 9-pixel biomolecular photoreceptor was fabricated with a sandwich-type structure of ITO/LB films/electrolyte gel/Pt. Since each functional molecule shows its own response characteristic according to the light illumination in the visible region, the simplified knowledge-based algorithm for interpretation of the incident light wavelength (color) was proposed based on the basic rule describing the relationship between the photoelectric response characteristics and the incident light wavelength. When simple color images were projected onto the photoreceptor, the primary colors in visible light region, red, green, and blue were clearly recognized, and the projected color images were fairly well reproduced onto the color monitor by the proposed photoreceptor with the knowledge-based algorithm. It is concluded that the proposed device has a capability of recognizing the color images and can be used as a model system to simulate the information processing function of the human visual system.     

A Novel Medical Image Protection Scheme Using a 3-Dimensional Chaotic System

Recently, great concerns have been raised regarding the issue of medical image protection due to the increasing demand for telemedicine services, especially the teleradiology service. To meet this challenge, a novel chaos-based approach is suggested in this paper. To address the security and efficiency problems encountered by many existing permutation-diffusion type image ciphers, the new scheme utilizes a single 3D chaotic system, Chen''s chaotic system, for both permutation and diffusion. In the permutation stage, we introduce a novel shuffling mechanism, which shuffles each pixel in the plain image by swapping it with another pixel chosen by two of the three state variables of Chen''s chaotic system. The remaining variable is used for quantification of pseudorandom keystream for diffusion. Moreover, the selection of state variables is controlled by plain pixel, which enhances the security against known/chosen-plaintext attack. Thorough experimental tests are carried out and the results indicate that the proposed scheme provides an effective and efficient way for real-time secure medical image transmission over public networks.     

Research on cascading high-dimensional isomorphic chaotic maps

In order to overcome the security weakness of the discrete chaotic sequence caused by small Lyapunov exponent and keyspace, a general chaotic construction method by cascading multiple high-dimensional isomorphic maps is presented in this paper. Compared with the original map, the parameter space of the resulting chaotic map is enlarged many times. Moreover, the cascaded system has larger chaotic domain and bigger Lyapunov exponents with proper parameters. In order to evaluate the effectiveness of the presented method, the generalized 3-D Hénon map is utilized as an example to analyze the dynamical behaviors under various cascade modes. Diverse maps are obtained by cascading 3-D Hénon maps with different parameters or different permutations. It is worth noting that some new dynamical behaviors, such as coexisting attractors and hyperchaotic attractors are also discovered in cascaded systems. Finally, an application of image encryption is delivered to demonstrate the excellent performance of the obtained chaotic sequences.     

An annealed chaotic maximum neural network for bipartite subgraph problem

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.     

Quaternion-based discriminant analysis method for color face recognition

Pattern recognition techniques have been used to automatically recognize the objects, personal identities, predict the function of protein, the category of the cancer, identify lesion, perform product inspection, and so on. In this paper we propose a novel quaternion-based discriminant method. This method represents and classifies color images in a simple and mathematically tractable way. The proposed method is suitable for a large variety of real-world applications such as color face recognition and classification of the ground target shown in multispectrum remote images. This method first uses the quaternion number to denote the pixel in the color image and exploits a quaternion vector to represent the color image. This method then uses the linear discriminant analysis algorithm to transform the quaternion vector into a lower-dimensional quaternion vector and classifies it in this space. The experimental results show that the proposed method can obtain a very high accuracy for color face recognition.     

Fast processing of microscopic images using object-based extended depth of field

Background

Microscopic analysis requires that foreground objects of interest, e.g. cells, are in focus. In a typical microscopic specimen, the foreground objects may lie on different depths of field necessitating capture of multiple images taken at different focal planes. The extended depth of field (EDoF) technique is a computational method for merging images from different depths of field into a composite image with all foreground objects in focus. Composite images generated by EDoF can be applied in automated image processing and pattern recognition systems. However, current algorithms for EDoF are computationally intensive and impractical, especially for applications such as medical diagnosis where rapid sample turnaround is important. Since foreground objects typically constitute a minor part of an image, the EDoF technique could be made to work much faster if only foreground regions are processed to make the composite image. We propose a novel algorithm called object-based extended depths of field (OEDoF) to address this issue.

Methods

The OEDoF algorithm consists of four major modules: 1) color conversion, 2) object region identification, 3) good contrast pixel identification and 4) detail merging. First, the algorithm employs color conversion to enhance contrast followed by identification of foreground pixels. A composite image is constructed using only these foreground pixels, which dramatically reduces the computational time.

Results

We used 250 images obtained from 45 specimens of confirmed malaria infections to test our proposed algorithm. The resulting composite images with all in-focus objects were produced using the proposed OEDoF algorithm. We measured the performance of OEDoF in terms of image clarity (quality) and processing time. The features of interest selected by the OEDoF algorithm are comparable in quality with equivalent regions in images processed by the state-of-the-art complex wavelet EDoF algorithm; however, OEDoF required four times less processing time.

Conclusions

This work presents a modification of the extended depth of field approach for efficiently enhancing microscopic images. This selective object processing scheme used in OEDoF can significantly reduce the overall processing time while maintaining the clarity of important image features. The empirical results from parasite-infected red cell images revealed that our proposed method efficiently and effectively produced in-focus composite images. With the speed improvement of OEDoF, this proposed algorithm is suitable for processing large numbers of microscope images, e.g., as required for medical diagnosis.

     

多普勒彩色血流成像中流速估计方法的研究

目的：探讨多普勒彩色血流成像中流速估计的方法。方法：对多普勒彩色血流成像中流速估计的两种算法-相域自相关和时域互相关进行了理论分析,在FieldII软件平台上对两种算法进行仿真。分别在中心流速为0．5m／s（中低速）和0．5m／s（高速）时进行血流速度仿真,得出了各自不同中心流速的血流速度分布曲线,并对其进行了对比分析。结果：相域自相关方法对中低速血流进行流速传计的精确度和稳健性都强于时域互相关方法;对于高速血流相域方法估计结果产生了混叠,但时域方法可以通过加大最值的搜索范围仍然能够得到正确的估计结果。结论：两种方法各有优缺点,互为补充。在实际应用中可以考虑结合使用两种方法,充分利用二者的优点。     

超声彩色血流成像的计算机快速仿真方法

研究超声彩色血流成像的快速仿真方法,克服原先仿真方法非常耗时的缺点。方法超声彩色血流成像计算机仿真中,血流信号是对成像区间内所有点散射体的回波信号累加而得到的。通过引入新的等效散射体模型,可以大大降低散射体的密度,从而减少计算回波信号所需时间。在计算机上用Matlab编程来进行仿真实验,对以往仿真方法和基于等效散射体模型方法的性能进行比较。结果实验表明:基于等效散射体模型的仿真,在保证相同流速精度的前提下,仿真速度比传统方法提高了10倍以上。结论基于等效散射体模型的仿真方法能极大地提高超声彩色血流成像的仿真速度,可以为超声彩色血流成像的方法研究提供便利。     

A new multi-population artificial bee algorithm based on global and local optima for numerical optimization

Artificial Bee Colony (ABC) algorithm is a nature-inspired algorithm that showed its efficiency for optimizations. However, the ABC algorithm showed some imbalances between exploration and exploitation. In order to improve the exploitation and enhance the convergence speed, a multi-population ABC algorithm based on global and local optimum (namely MPGABC) is proposed in this paper. First, in MPGABC, the initial population is generated using both chaotic systems and opposition-based learning methods. The colony in MPGABC is divided into several sub-populations to increase diversity. Moreover, the solution search mechanism is modified by introducing global and local optima in the solution search equations of both employed and onlookers. The scout bees in the proposed algorithm are generated similarly to the initial population. Finally, the proposed algorithm is compared with several state-of-art ABC algorithm variants on a set of 13 classical benchmark functions. The experimental results show that MPGABC competes and outperforms other ABC algorithm variants.

     

Parameter Estimation of Fractional-Order Chaotic Systems by Using Quantum Parallel Particle Swarm Optimization Algorithm

Parameter estimation for fractional-order chaotic systems is an important issue in fractional-order chaotic control and synchronization and could be essentially formulated as a multidimensional optimization problem. A novel algorithm called quantum parallel particle swarm optimization (QPPSO) is proposed to solve the parameter estimation for fractional-order chaotic systems. The parallel characteristic of quantum computing is used in QPPSO. This characteristic increases the calculation of each generation exponentially. The behavior of particles in quantum space is restrained by the quantum evolution equation, which consists of the current rotation angle, individual optimal quantum rotation angle, and global optimal quantum rotation angle. Numerical simulation based on several typical fractional-order systems and comparisons with some typical existing algorithms show the effectiveness and efficiency of the proposed algorithm.     

Distributed Biomedical Scheme for Controlled Recovery of Medical Encrypted Images

With an advancement in biomedical applications, many images are communicated over the public networks. Therefore, these medical images are prone to various security threats. Development of end to end secure communication protocol for these medical images is found to be a challenging task. Therefore, many researchers have proposed various image medica image encryption techniques to provide end to end security of medical images. However, the existing approaches of block-based recovery of the secret through progressive sharing paradigm have support for limited threshold value of the chosen blocks out of the total number of the blocks during the communication of the image. Most of the suggested scheme has fixed threshold value for the blocks during recovery of secret; works good for a limited threshold (k) value out of number of blocks (n) in which secret has been divided for security. A novel threshold based (any value of k and n) blockwide recovery of secret in progressive secret sharing has been introduced and analyzed for distributed environment. The proposed threshold block wise splitting using progressive visual secret sharing (T-BPVSS) achieves any general higher value of threshold for recovery of secret medical images. Proposed scheme is tested based on various parameters such as varying values of threshold for recovery of secret during enhanced security scenario, as well as changing dimensions of the images and introducing noise in the images. A detailed distributed computing recovery solution is also suggested for the original secret by using distribution technique of shares across the networks of computers. The scheme satisfies for perfect security condition in distributed environment using at least minimum decided threshold numbers of participants (k) before revealing any of the blocks of secret medical image.     

A Secure and Robust Compressed Domain Video Steganography for Intra- and Inter-Frames Using Embedding-Based Byte Differencing (EBBD) Scheme

This paper presents a novel secure and robust steganographic technique in the compressed video domain namely embedding-based byte differencing (EBBD). Unlike most of the current video steganographic techniques which take into account only the intra frames for data embedding, the proposed EBBD technique aims to hide information in both intra and inter frames. The information is embedded into a compressed video by simultaneously manipulating the quantized AC coefficients (AC-QTCs) of luminance components of the frames during MPEG-2 encoding process. Later, during the decoding process, the embedded information can be detected and extracted completely. Furthermore, the EBBD basically deals with two security concepts: data encryption and data concealing. Hence, during the embedding process, secret data is encrypted using the simplified data encryption standard (S-DES) algorithm to provide better security to the implemented system. The security of the method lies in selecting candidate AC-QTCs within each non-overlapping 8 × 8 sub-block using a pseudo random key. Basic performance of this steganographic technique verified through experiments on various existing MPEG-2 encoded videos over a wide range of embedded payload rates. Overall, the experimental results verify the excellent performance of the proposed EBBD with a better trade-off in terms of imperceptibility and payload, as compared with previous techniques while at the same time ensuring minimal bitrate increase and negligible degradation of PSNR values.     

数据库安全性研究

论述了数据库安全的概念、数据库安全性的要求和数据库基本安全结构以及数据库安全性的实现方法,实现数据存储的安全保护和数据库加密。     

Accelerating an Ordered-Subset Low-Dose X-Ray Cone Beam Computed Tomography Image Reconstruction with a Power Factor and Total Variation Minimization

In recent years, there has been increased interest in low-dose X-ray cone beam computed tomography (CBCT) in many fields, including dentistry, guided radiotherapy and small animal imaging. Despite reducing the radiation dose, low-dose CBCT has not gained widespread acceptance in routine clinical practice. In addition to performing more evaluation studies, developing a fast and high-quality reconstruction algorithm is required. In this work, we propose an iterative reconstruction method that accelerates ordered-subsets (OS) reconstruction using a power factor. Furthermore, we combine it with the total-variation (TV) minimization method. Both simulation and phantom studies were conducted to evaluate the performance of the proposed method. Results show that the proposed method can accelerate conventional OS methods, greatly increase the convergence speed in early iterations. Moreover, applying the TV minimization to the power acceleration scheme can further improve the image quality while preserving the fast convergence rate.     

低频电流场颅内异物检测技术重建算法的研究

电磁场数值计算方法可用于检测颅内异物。使用的重建算法有拟牛顿法、Bulirsch-Stoer外推法、局部加速收敛法。这些算法对改善重建计算的精度起着至关重要的作用。最后,仿真计算说明算法是有效的。     

Attack and improvement of the recent identity-based encryption with authorized equivalence test in cluster computing

Recently, Elhabob et al. proposed an identity-based encryption with authorized equivalence test (IBE-AET), which allows authorized testers to check whether messages in two ciphertexts are the same or not under the identity-based setting (Cluster Computing, 2020). This paper looks into the security and correctness of their IBE-AET construction. More specifically, contrary to the security claim in the original paper, we point out that their proposed scheme cannot achieve the indistinguishability under adaptively chosen identity and ciphertext attacks (IND-ID-CCA2) for adversaries who do not have authorization. In terms of the correctness of the scheme, we also identify that their type-4 authorization does not work correctly. Finally, we remedy their construction in order that it satisfies the IND-ID-CCA2 security with the rigorous security proof as well as the type-4 authorization works correctly.