•This study aims to provide a fast secure multiple-image encryption (MIE) algorithm.•Image matrix indexes and DNA sequence are basis of the proposed algorithm.•Proposed algorithm is fast and secure.
...To improve the encryption quality and increase the speed of transmission over the internet, this study aims to provide a fast secure multiple-image encryption (MIE) algorithm based on DNA sequence and image matrix indexes. Because multiple images are considered in the proposed MIE algorithm, one big concern refers to the speed of the algorithm. In the first phase of the proposed method, multiple plain- images are attached together to create a single image. Next, this image is converted to one-dimension array. Half of the array indexes are used to permute all the pixels position. During the permutation, the same indexes are associated with DNA sequence to diffuse the pixels gray level. Simulation results demonstrate that using half of indexes for permutation and diffusion make the proposed algorithm very fast and also using DNA sequence encoding gives the algorithm enough power to resist against common attacks in the era of image encryption.
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The security of digital images has attracted much attention recently. In this study, a new method based on a hybrid model is proposed for image encryption. The hybrid model is composed of a genetic ...algorithm and a chaotic function. In the first stage of the proposed method, a number of encrypted images are constructed using the original image and the chaotic function. In the next stage, these encrypted images are used as the initial population for the genetic algorithm. In each stage of the genetic algorithm, the answer obtained from the previous iteration is optimized to produce the best-encrypted image. The best-encrypted image is defined as the image with the highest entropy and the lowest correlation coefficient among adjacent pixels.
The use of genetic algorithms in image encryption has been attempted for the first time in this paper. Analyzing the results from the performed experiments, a high level of resistance of the proposed method against brute-force and statistical invasions is obviously illustrated. The obtained entropy and correlation coefficients of the method are approximately 7.9978 and −0.0009, respectively.
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This paper proposes a novel algorithm for encrypting color images. The innovation in this study is the use of messenger ribonucleic acid (mRNA) encoding to import into Deoxyribonucleic acid (DNA) ...encoding. For permutation of the plain image bits, we use Arnold’s Cat Map at the bit-level. Then, using Non-Adjacent Coupled Map Lattices (NCML), we apply diffusion operations to the permuted color channels. We also provide the upgrade of the diffusion phase with DNA encoding. In the proposed algorithm, the choices are random depending on the secret key, which is implemented using a simple logistic map. Hashing the string entered by the user, the secret key, parameters, and initial values are generated by the Double MD5 method. The results of tests and security analysis showed that the results of encryption with this scheme are effective, and the key space is large enough to withstand common attacks.
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The Vehicle Routing Problem (VRP) holds significant importance in operational research as it deals with optimizing the delivery routes of vehicles to efficiently serve a set of customers. One ...well-known variant of VRP is the Capacitated Vehicle Routing Problem (CVRP), where the objective is to determine a set of routes for a fleet of identical vehicles, starting and ending at a central depot, while respecting capacity constraints and minimizing total distance traveled. This paper introduces a novel hybrid metaheuristic, named Dynamic Population Island GA and Hybrid Genetic Search (DPIGA-HGS), to tackle the CVRP. DPIGA-HGS combines the strengths of the proposed Dynamic Population Island GA (DPIGA) and Hybrid Genetic Search (HGS) as its local search engine within each island. DPIGA is a specialized variant of Island Genetic Algorithm (IGA) that allows islands to lose their populations over time. In the work herein, DPIGA-HGS is shown to outperform existing state-of-the-art algorithms from the literature. It achieves higher quality solutions, leading to a notable increase in the number of Best-Known Solutions (BKS) found and reduced average and maximum solution gaps compared to BKS. The algorithm's effectiveness is demonstrated through several experiments on diverse benchmark instances, including classical benchmarks (Uchoa, CMT, and Golden) and real-world application instances (LoggiBUD).
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Nowadays, security in data transfer is of special importance. Images are of the most attractive kinds of data in the encryption domain. Color images are more attractive than the gray-level images due ...to provision of more information. In the present study, various existing color (RGB mode) image encryption schemes have been examined comprehensively based on the application domains in addition to summarizing over 50 studies in this field, most of which being published in the last year. In addition, in this study, color image encryption has been categorized into ten schemes, then the proposed schemes have been compared and their advantages and limitations have been highlighted. Moreover, a complete list of common security analysis techniques for (gray or color) image encryption has been discussed which are capable of evaluating the method potential resistance to different possible attacks. The present study has been carried out to provide detailed knowledge regarding the existing image encryption schemes in the area of the RGB images. Finally, in the current study, various open issues and research directions have been considered in order to explore the promising areas for future developments.
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A new evolutionary-based image encryption method is proposed to protect the image content against adversary attacks from an insecure network throughout the Internet. Two-dimensional Henon chaotic map ...is the significant part of the encryption process, whereas its performance strongly depends on the fine tuning of its parameters, including
α
and
β
. Imperialist Competitive Algorithm (ICA) is applied to determine these parameters based on the input simple image, so that the pseudorandom number generated by the two-dimensional Henon map would be unique for each simple image, making it difficult to explore the encryption process. Experimental results assert that the proposed method is secure enough to resist against common attacks.
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In recent years, the security of digital images has constantly been a major topic discussed by researchers. In this paper, we proposed a new structure for image encryption using Deoxyribonucleic Acid ...(DNA) and Recursive Cellular Automata (RCA). Image encryption takes place in two separate phases. At the permutation phase, a logistic map is employed for cellular shift in the image rows and columns. Then, the DNA and RCA at the diffusion phase are used to change the gray level of pixels to new values. The optimum entropy value obtained in this method was 7.9994 while the correlation coefficient was 0.0001, which indicated good results. Moreover, the newly proposed technique was demonstrated to enhance resistance against a variety of attacks through desirable image encryption.
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Feature selection is the problem of finding the best subset of features which have the most impact in predicting class labels. It is noteworthy that application of feature selection is more valuable ...in high dimensional datasets. In this paper, a filter feature selection method has been proposed on high dimensional binary medical datasets – Colon, Central Nervous System (CNS), GLI_85, SMK_CAN_187. The proposed method incorporates three sections. First, whale algorithm has been used to discard irrelevant features. Second, the rest of features are ranked based on a frequency based heuristic approach called Mutual Congestion. Third, majority voting has been applied on best feature subsets constructed using forward feature selection with threshold τ = 10. This work provides evidence that Mutual Congestion is solely powerful to predict class labels. Furthermore, applying whale algorithm increases the overall accuracy of Mutual Congestion in most of the cases. The findings also show that the proposed method improves the prediction with selecting the less possible features in comparison with state of the arts.
https://github.com/hnematzadeh
•A novel feature selection method based on evolutionary algorithm•Proposing Mutual Congestion as new method for labelling a class•Applying whale algorithm to increase the overall accuracy of Mutual Congestion
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Gene selection is the process of selecting the optimal feature subset in an arbitrary dataset. The significance of gene selection is in high dimensional datasets in which the number of samples and ...features are low and high respectively. The major goals of gene selection are increasing the accuracy, finding the minimal effective feature subset, and increasing the performance of evaluations. This paper proposed two heuristic methods for gene selection, namely, Xvariance against Mutual Congestion. Xvariance tries to classify labels using internal attributes of features however Mutual Congestion is frequency based. The proposed methods have been conducted on eight binary medical datasets. Results reveal that Xvariance works well with standard datasets, however Mutual Congestion improves the accuracy of high dimensional datasets considerably.
•Proposing two heuristic methods for gene selection.•Xvariance tries to classify labels using internal attributes of features.•Mutual Congestion is frequency based feature selection method.
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In the past decade, the interest on digital images security has been increased among scientists. A synchronous permutation and diffusion technique is designed in order to protect gray-level image ...content while sending it through internet. To implement the proposed method, two-dimensional plain-image is converted to one dimension. Afterward, in order to reduce the sending process time, permutation and diffusion steps for any pixel are performed in the same time. The permutation step uses chaotic map and deoxyribonucleic acid (DNA) to permute a pixel, while diffusion employs DNA sequence and DNA operator to encrypt the pixel. Experimental results and extensive security analyses have been conducted to demonstrate the feasibility and validity of this proposed image encryption method.
•This paper uses 3D logistic map and DNA sequence to do encryption.•A synchronous permutation-diffusion technique has been developed.•3D logistic map is used to do permutation and part of diffusion.•The proposed method is very fast and efficient.
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