Publication Date: 2024
Journal of Information Security and Applications (22142134)83
Today, due to the unparalleled growth of multimedia data sharing, especially digital images, between users over insecure channels in real-time applications, cryptography algorithms have gained increasing attention for the secure and efficient transmission. In classical chaos-based image cryptosystems, the confusion and diffusion operations are often applied as two separate and independent phases, which threatens the cryptosystem security. To address these problems, in this paper, a fast image cryptosystem based on parallel simultaneous diffusion–confusion strategy has been proposed using Latin squares, called PSDCLS. It consists of three main steps. First, the initial parameters of the Hénon-Sine chaotic map are produced from SHA256 of both the plain image content and the user's secret key. Second, a chaos-based random Latin square is constructed by employing the chaotic sequence produced through the Hénon-Sine chaotic map. Third, a parallel simultaneous diffusion–confusion scheme is proposed by using Latin square and vectorization technique to overcome the problems of computational complexity and high risk of separable and iterative confusion–diffusion operations in the classical chaos-based image cryptosystems. To analyze and evaluate the security and performance of PSDCLS cryptosystem, we conducted extensive simulations and experiments on various benchmark images. Experimental results and analyses show that PSDCLS achieves excellent scores for information entropy (>7.99), correlation coefficients close to 0, key space (2512), NPCR (>99.60%), UACI (>33.46%). The encryption time for test images of size 512 × 512 and 512×512×3 was around 0.026 and 0.081 s, respectively. Therefore, PSDCLS is highly robust against common cryptographic attacks and serves as a swift cryptosystem for real-time encryption applications. The source code of PSDCLS is accessible at: https://github.com/EbrahimZarei64/PSDCLS. © 2024 Elsevier Ltd
Publication Date: 2020
Multimedia Tools and Applications (13807501)79(33-34)pp. 24993-25022
In this paper, we propose a novel image encryption scheme based on a hybrid model of DNA computing, chaotic systems and hash functions. The significant advantage of the proposed scheme is high efficiency. The proposed scheme consists of the DNA level permutation and diffusion. In the DNA level permutation, a mapping function based on the logistic map is applied on the DNA image to randomly change the position of elements in the DNA image. In the DNA level diffusion, not only we define two new algebraic DNA operators, called the DNA left-circular shift and DNA right-circular shift, but we also use a variety of DNA operators to diffuse the permutated DNA image with the key DNA image. The experimental results and security analyses indicate that the proposed image encryption scheme not only has good encryption effect and able to resist against the known attacks, but also is sufficiently fast for practical applications. The MATLAB source code of the proposed image encryption scheme is publicly available at the URL: https://github.com/EbrahimZarei64/ImageEncryption. © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
Publication Date: 2019
Journal of Parallel and Distributed Computing (07437315)129pp. 14-35
Nested loops are main source of the parallelism in many scientific applications. Partitioning the iteration space of nested loops with data dependencies into tiles and assigning them to processing nodes for parallel execution is essential for achieving high performance. Although most of the previous work focused on tiling on fully connected homogeneous distributed systems, some studies have been devoted to tiling on partially connected distributed systems. In this paper, we address the parallelization of perfectly nested loops with dependencies on partially connected heterogeneous distributed systems and present a topology and computational-power aware tile mapping. This work aims to take into account not only the node's computational power when tiling iteration space of nested loops but also the exploitation of the network topology when mapping tiles to processing nodes. This approach allows minimizing the parallel execution time by improving the load balancing and minimizing the communication costs. We demonstrate the performance of proposed method by comparing it with the computational-power aware tile mapping and the topology aware tile mapping. The experimental results show that the proposed method improves the parallel execution time by up to 62% and 28% compared with the computational-power aware tile mapping and the topology aware tile mapping, respectively. © 2019 Elsevier Inc.
Publication Date: 2017
Concurrency and Computation: Practice and Experience (15320626)29(5)
Nested loops are the largest source of parallelism in many data-parallel scientific applications. Heterogeneous distributed systems are popular computing platforms for data-parallel applications. Data partitioning is critical in exploiting the computational power of such systems, and existing data partitioning algorithms try to maximize performance of data-parallel applications by finding a data distribution that balances the workload between the processing nodes while minimizing communication costs. This paper addresses the problem of 3-dimensional data partitioning for 3-level perfectly nested loops on heterogeneous distributed systems. The primary aim is to minimize the execution time by improving the load balancing and minimizing the internode communications. We propose a new data partitioning algorithm using dynamic programming, build a theoretical model to estimate the execution time of each partition, and select a partition with minimum execution time as a near-optimal solution. We demonstrate the effectiveness of the new algorithm for 2 data-parallel scientific applications on heterogeneous distributed systems. The new algorithm reduces the execution time by between 7% and 17%, on average, compared with leading data partitioning methods on 3 heterogeneous distributed systems. Copyright © 2016 John Wiley & Sons, Ltd.
Publication Date: 2016
Scalable Computing (18951767)17(4)pp. 331-349
Nested loops are one of the most time-consuming parts and the largest sources of parallelism in many scientific applications. In this paper, we address the problem of 3-dimensional tiling and scheduling of three-level perfectly nested loops with dependencies on heterogeneous systems. To exploit the parallelism, we tile and schedule nested loops with dependencies by awareness of computational power of the processing nodes and execute them in pipeline mode. The tile size plays an important role to improve the parallel execution time of nested loops. We develop and evaluate a theoretical model to estimate the parallel execution time of tilled nested loops. Also, we propose a tiling genetic algorithm that used the proposed model to find the near-optimal tile size, minimizing the parallel execution time of dependence nested loops. We demonstrate the accuracy of theoretical model and effectiveness of the proposed tiling genetic algorithm by several experiments on heterogeneous systems. The 3D tiling reduces the parallel execution time by a factor of 1.2× to 2× over the 2D tiling, while parallelizing 3D heat equation as a benchmark. © 2016 SCPE.
Publication Date: 2015
Malaysian Journal Of Computer Science (01279084)28(1)pp. 46-58
Image reconstruction is an important part of computed tomography imaging systems, which converts the measured data into images. Because of high computational cost and slow convergence of iterative reconstruction algorithms, these methods are not widely used in practice. In this paper, we propose a hybrid iterative algorithm by combining multigrid method,Tikhonov regularization and Simultaneous Iterative Reconstruction Technique (SIRT) for reconstruction of the computed tomography image that reduces this drawback. To do so, we reduce the time and the volume of computations considerably by finding astable and appropriate starting point. The experimental results indicate that the proposed iterative algorithm has more rapid convergence and reconstructs high quality images in short computational time than the classical ones.
This paper presents a novel image security system based on the replacement of the pixel values using recursive Cellular automata (CA) substitution. The advantages of our proposed method are that it is computationally efficient and it is reasonably passing sensibility analysis tests. The proposed method is carried out by using one half of image data to encrypt the other half of the image mutually. Our algorithm can encrypt image in parallel and be also applied to color image encryption. In this proposed method, size of key is dynamic and by changing a bit of security key the image cannot retrieve because our method is key sensitive. Simulation results obtained using color; white-black and gray-level images demonstrate the good performance of the proposed image security system. © 2011 IEEE.
