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  • Open Access

    ARTICLE

    Hardware-Enabled Key Generation in Industry 4.0 Cryptosystems through Analog Hyperchaotic Signals

    Borja Bordel Sánchez1,*, Fernando Rodríguez-Sela1, Ramón Alcarria2, Tomás Robles1

    CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1821-1853, 2025, DOI:10.32604/cmc.2025.059012 - 16 April 2025

    Abstract The Industry 4.0 revolution is characterized by distributed infrastructures where data must be continuously communicated between hardware nodes and cloud servers. Specific lightweight cryptosystems are needed to protect those links, as the hardware node tends to be resource-constrained. Then Pseudo Random Number Generators are employed to produce random keys, whose final behavior depends on the initial seed. To guarantee good mathematical behavior, most key generators need an unpredictable voltage signal as input. However, physical signals evolve slowly and have a significant autocorrelation, so they do not have enough entropy to support high-randomness seeds. Then, electronic… More >

  • Open Access

    ARTICLE

    Chaos-Based Novel Watermarked Satellite Image Encryption Scheme

    Mohamed Medani1, Yahia Said2, Nashwan Adnan Othman3,4, Farrukh Yuldashev5, Mohamed Kchaou6, Faisal Khaled Aldawood6, Bacha Rehman7,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 1049-1070, 2025, DOI:10.32604/cmes.2025.063405 - 11 April 2025

    Abstract Satellite images are widely used for remote sensing and defence applications, however, they are subject to a variety of threats. To ensure the security and privacy of these images, they must be watermarked and encrypted before communication. Therefore, this paper proposes a novel watermarked satellite image encryption scheme based on chaos, Deoxyribonucleic Acid (DNA) sequence, and hash algorithm. The watermark image, DNA sequence, and plaintext image are passed through the Secure Hash Algorithm (SHA-512) to compute the initial condition (keys) for the Tangent-Delay Ellipse Reflecting Cavity Map (TD-ERCS), Henon, and Duffing chaotic maps, respectively. Through More >

  • Open Access

    ARTICLE

    Efficient Bit-Plane Based Medical Image Cryptosystem Using Novel and Robust Sine-Cosine Chaotic Map

    Zeric Tabekoueng Njitacke1, Louai A. Maghrabi2, Musheer Ahmad3,*, Turki Althaqafi4

    CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 917-933, 2025, DOI:10.32604/cmc.2025.059640 - 26 March 2025

    Abstract This paper presents a high-security medical image encryption method that leverages a novel and robust sine-cosine map. The map demonstrates remarkable chaotic dynamics over a wide range of parameters. We employ nonlinear analytical tools to thoroughly investigate the dynamics of the chaotic map, which allows us to select optimal parameter configurations for the encryption process. Our findings indicate that the proposed sine-cosine map is capable of generating a rich variety of chaotic attractors, an essential characteristic for effective encryption. The encryption technique is based on bit-plane decomposition, wherein a plain image is divided into distinct… More >

  • Open Access

    ARTICLE

    Sensitivity Analysis of Structural Dynamic Behavior Based on the Sparse Polynomial Chaos Expansion and Material Point Method

    Wenpeng Li1, Zhenghe Liu1, Yujing Ma1, Zhuxuan Meng2,*, Ji Ma3, Weisong Liu2, Vinh Phu Nguyen4

    CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1515-1543, 2025, DOI:10.32604/cmes.2025.059235 - 27 January 2025

    Abstract This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior. Physical models involving deformation, such as collisions, vibrations, and penetration, are developed using the material point method. To reduce the computational cost of Monte Carlo simulations, response surface models are created as surrogate models for the material point system to approximate its dynamic behavior. An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order, effectively balancing the accuracy and computational efficiency of the surrogate model. Based on the sparse polynomial More >

  • Open Access

    ARTICLE

    AI-Powered Image Security: Utilizing Autoencoders for Advanced Medical Image Encryption

    Fehaid Alqahtani*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1709-1724, 2024, DOI:10.32604/cmes.2024.054976 - 27 September 2024

    Abstract With the rapid advancement in artificial intelligence (AI) and its application in the Internet of Things (IoT), intelligent technologies are being introduced in the medical field, giving rise to smart healthcare systems. The medical imaging data contains sensitive information, which can easily be stolen or tampered with, necessitating secure encryption schemes designed specifically to protect these images. This paper introduces an artificial intelligence-driven novel encryption scheme tailored for the secure transmission and storage of high-resolution medical images. The proposed scheme utilizes an artificial intelligence-based autoencoder to compress high-resolution medical images and to facilitate fast encryption… More >

  • Open Access

    ARTICLE

    A Non-Intrusive Stochastic Phase-Field for Fatigue Fracture in Brittle Materials with Uncertainty in Geometry and Material Properties

    Rajan Aravind1,2, Sundararajan Natarajan1, Krishnankutty Jayakumar2, Ratna Kumar Annabattula1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 997-1032, 2024, DOI:10.32604/cmes.2024.053047 - 27 September 2024

    Abstract Understanding the probabilistic nature of brittle materials due to inherent dispersions in their mechanical properties is important to assess their reliability and safety for sensitive engineering applications. This is all the more important when elements composed of brittle materials are exposed to dynamic environments, resulting in catastrophic fatigue failures. The authors propose the application of a non-intrusive polynomial chaos expansion method for probabilistic studies on brittle materials undergoing fatigue fracture when geometrical parameters and material properties are random independent variables. Understanding the probabilistic nature of fatigue fracture in brittle materials is crucial for ensuring the… More >

  • Open Access

    ARTICLE

    Multi-Level Image Segmentation Combining Chaotic Initialized Chimp Optimization Algorithm and Cauchy Mutation

    Shujing Li, Zhangfei Li, Wenhui Cheng, Chenyang Qi, Linguo Li*

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2049-2063, 2024, DOI:10.32604/cmc.2024.051928 - 15 August 2024

    Abstract To enhance the diversity and distribution uniformity of initial population, as well as to avoid local extrema in the Chimp Optimization Algorithm (CHOA), this paper improves the CHOA based on chaos initialization and Cauchy mutation. First, Sin chaos is introduced to improve the random population initialization scheme of the CHOA, which not only guarantees the diversity of the population, but also enhances the distribution uniformity of the initial population. Next, Cauchy mutation is added to optimize the global search ability of the CHOA in the process of position (threshold) updating to avoid the CHOA falling More >

  • Open Access

    ARTICLE

    Arrhythmia Detection by Using Chaos Theory with Machine Learning Algorithms

    Maie Aboghazalah1,*, Passent El-kafrawy2, Abdelmoty M. Ahmed3, Rasha Elnemr5, Belgacem Bouallegue3, Ayman El-sayed4

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 3855-3875, 2024, DOI:10.32604/cmc.2023.039936 - 20 June 2024

    Abstract Heart monitoring improves life quality. Electrocardiograms (ECGs or EKGs) detect heart irregularities. Machine learning algorithms can create a few ECG diagnosis processing methods. The first method uses raw ECG and time-series data. The second method classifies the ECG by patient experience. The third technique translates ECG impulses into Q waves, R waves and S waves (QRS) features using richer information. Because ECG signals vary naturally between humans and activities, we will combine the three feature selection methods to improve classification accuracy and diagnosis. Classifications using all three approaches have not been examined till now. Several More >

  • Open Access

    ARTICLE

    Sensitivity Analysis of Electromagnetic Scattering from Dielectric Targets with Polynomial Chaos Expansion and Method of Moments

    Yujing Ma1,4, Zhongwang Wang2, Jieyuan Zhang3, Ruijin Huo1,4, Xiaohui Yuan1,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2079-2102, 2024, DOI:10.32604/cmes.2024.048488 - 20 May 2024

    Abstract In this paper, an adaptive polynomial chaos expansion method (PCE) based on the method of moments (MoM) is proposed to construct surrogate models for electromagnetic scattering and further sensitivity analysis. The MoM is applied to accurately solve the electric field integral equation (EFIE) of electromagnetic scattering from homogeneous dielectric targets. Within the bistatic radar cross section (RCS) as the research object, the adaptive PCE algorithm is devoted to selecting the appropriate order to construct the multivariate surrogate model. The corresponding sensitivity results are given by the further derivative operation, which is compared with those of More >

  • Open Access

    PROCEEDINGS

    The Method of Moments for Electromagnetic Scattering Analysis Accelerated by the Polynomial Chaos Expansion in Infinite Domains

    Yujing Ma1,*, Leilei Chen2,3, Haojie Lian3,4, Zhongwang Wang2,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.28, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.010585

    Abstract An efficient method of moments (MoM) based on polynomial chaos expansion(PCE) is applied to quickly calculate the electromagnetic scattering problems. The triangle basic functions are used to discretize the surface integral equations. The PCE is utilized to accelerate the MoM by constructing a surrogate model for univariate and bivariate analysis[1]. The mathematical expressions of the surrogate model for the radar cross-section (RCS) are established by considering uncertain parameters such as bistatic angle, incident frequency, and dielectric constant[2,3]. By using the example of a scattering cylinder with analytical solution, it is verified that the MoM accelerated More >

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