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  • Open Access

    ARTICLE

    Enhanced Heap-Based Optimizer Algorithm for Solving Team Formation Problem

    Nashwa Nageh1, Ahmed Elshamy1, Abdel Wahab Said Hassan1, Mostafa Sami2, Mustafa Abdul Salam3,4,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5245-5268, 2022, DOI:10.32604/cmc.2022.030906 - 28 July 2022

    Abstract Team Formation (TF) is considered one of the most significant problems in computer science and optimization. TF is defined as forming the best team of experts in a social network to complete a task with least cost. Many real-world problems, such as task assignment, vehicle routing, nurse scheduling, resource allocation, and airline crew scheduling, are based on the TF problem. TF has been shown to be a Nondeterministic Polynomial time (NP) problem, and high-dimensional problem with several local optima that can be solved using efficient approximation algorithms. This paper proposes two improved swarm-based algorithms for… More >

  • Open Access

    ARTICLE

    Chaotic Krill Herd with Deep Transfer Learning-Based Biometric Iris Recognition System

    Harbi Al-Mahafzah1, Tamer AbuKhalil1, Bassam A. Y. Alqaralleh2,*

    CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5703-5715, 2022, DOI:10.32604/cmc.2022.030399 - 28 July 2022

    Abstract Biometric verification has become essential to authenticate the individuals in public and private places. Among several biometrics, iris has peculiar features and its working mechanism is complex in nature. The recent developments in Machine Learning and Deep Learning approaches enable the development of effective iris recognition models. With this motivation, the current study introduces a novel Chaotic Krill Herd with Deep Transfer Learning Based Biometric Iris Recognition System (CKHDTL-BIRS). The presented CKHDTL-BIRS model intends to recognize and classify iris images as a part of biometric verification. To achieve this, CKHDTL-BIRS model initially performs Median Filtering More >

  • Open Access

    ARTICLE

    Cuckoo Optimized Convolution Support Vector Machine for Big Health Data Processing

    Eatedal Alabdulkreem1, Jaber S. Alzahrani2, Majdy M. Eltahir3, Abdullah Mohamed4, Manar Ahmed Hamza5,*, Abdelwahed Motwakel5, Mohamed I. Eldesouki6, Mohammed Rizwanullah5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3039-3055, 2022, DOI:10.32604/cmc.2022.029835 - 16 June 2022

    Abstract Big health data collection and storing for further analysis is a challenging task because this knowledge is big and has many features. Several cloud-based IoT health providers have been described in the literature previously. Furthermore, there are a number of issues related to time consumed and overall network performance when it comes to big data information. In the existing method, less performed optimization algorithms were used for optimizing the data. In the proposed method, the Chaotic Cuckoo Optimization algorithm was used for feature selection, and Convolutional Support Vector Machine (CSVM) was used. The research presents… More >

  • Open Access

    ARTICLE

    Encryption Algorithm for Securing Non-Disclosure Agreements in Outsourcing Offshore Software Maintenance

    Atif Ikram1,2,*, Masita Abdul Jalil1, Amir Bin Ngah1, Nadeem Iqbal2, Nazri Kama4, Azri Azmi4, Ahmad Salman Khan3, Yasir Mahmood3,4, Assad Alzayed5

    CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3827-3845, 2022, DOI:10.32604/cmc.2022.029609 - 16 June 2022

    Abstract Properly created and securely communicated, non-disclosure agreement (NDA) can resolve most of the common disputes related to outsourcing of offshore software maintenance (OSMO). Occasionally, these NDAs are in the form of images. Since the work is done offshore, these agreements or images must be shared through the Internet or stored over the cloud. The breach of privacy, on the other hand, is a potential threat for the image owners as both the Internet and cloud servers are not void of danger. This article proposes a novel algorithm for securing the NDAs in the form of… More >

  • Open Access

    ARTICLE

    Image Encryption Algorithm Based on New Fractional Beta Chaotic Maps

    Rabha W. Ibrahim1,*, Hayder Natiq2, Ahmed Alkhayyat3, Alaa Kadhim Farhan4, Nadia M. G. Al-Saidi5, Dumitru Baleanu6,7,8

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 119-131, 2022, DOI:10.32604/cmes.2022.018343 - 02 June 2022

    Abstract In this study, a new algorithm of fractional beta chaotic maps is proposed to generate chaotic sequences for image encryption. The proposed technique generates multi random sequences by shuffling the image pixel position. This technique is used to blur the pixels connecting the input and encrypted images and to increase the attack resistance. The proposed algorithm makes the encryption process sophisticated by using fractional chaotic maps, which hold the properties of pseudo-randomness. The fractional beta sequences are utilized to alter the image pixels to decryption attacks. The experimental results proved that the proposed image encryption More >

  • Open Access

    ARTICLE

    Chaotic Krill Herd with Fuzzy Based Routing Protocol for Wireless Networks

    Ashit Kumar Dutta1,*, Yasser Albagory2, Farhan M. Obesat3, Anas Waleed Abulfaraj4

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1659-1674, 2022, DOI:10.32604/iasc.2022.026263 - 25 May 2022

    Abstract Energy is considered a valuable source in wireless sensor networks (WSN) for effectively improving the survivability of the network. The non-uniform dispersion of load in the network causes unbalanced energy dissipation which can result in network interruption. The route selection process can be considered as an optimization problem and is solved by utilize of artificial intelligence (AI) techniques. This study introduces an energy efficient chaotic krill herd algorithm with adaptive neuro fuzzy inference system based routing (EECKHA-ANFIS) protocol for WSN. The goal of the EECKHA-ANFIS method is for deriving a better set of routes to… More >

  • Open Access

    ARTICLE

    A Highly Secured Image Encryption Scheme using Quantum Walk and Chaos

    Muhammad Islam Kamran1, Muazzam A. Khan1, Suliman A. Alsuhibany2, Yazeed Yasin Ghadi3, Arshad4, Jameel Arif1, Jawad Ahmad5,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 657-672, 2022, DOI:10.32604/cmc.2022.028876 - 18 May 2022

    Abstract The use of multimedia data sharing has drastically increased in the past few decades due to the revolutionary improvements in communication technologies such as the 4th generation (4G) and 5th generation (5G) etc. Researchers have proposed many image encryption algorithms based on the classical random walk and chaos theory for sharing an image in a secure way. Instead of the classical random walk, this paper proposes the quantum walk to achieve high image security. Classical random walk exhibits randomness due to the stochastic transitions between states, on the other hand, the quantum walk is more… More >

  • Open Access

    ARTICLE

    A Secure and Lightweight Chaos Based Image Encryption Scheme

    Fadia Ali Khan1, Jameel Ahmed1, Fehaid Alqahtani2, Suliman A. Alsuhibany3, Fawad Ahmed4, Jawad Ahmad5,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 279-294, 2022, DOI:10.32604/cmc.2022.028789 - 18 May 2022

    Abstract In this paper, we present an image encryption scheme based on the multi-stage chaos-based image encryption algorithm. The method works on the principle of confusion and diffusion. The proposed scheme containing both confusion and diffusion modules are highly secure and effective as compared to the existing schemes. Initially, an image (red, green, and blue components) is partitioned into blocks with an equal number of pixels. Each block is then processed with Tinkerbell Chaotic Map (TBCM) to get shuffled pixels and shuffled blocks. Composite Fractal Function (CFF) change the value of pixels of each color component More >

  • Open Access

    ARTICLE

    Secure Communication Scheme based on A New Hyperchaotic System

    Khaled Benkouider1, Aceng Sambas2, Ibrahim Mohammed Sulaiman3, Mustafa Mamat4, Kottakkaran Sooppy Nisar5,*

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1019-1035, 2022, DOI:10.32604/cmc.2022.025836 - 18 May 2022

    Abstract This study introduces a new continuous time differential system, which contains ten terms with three quadratic nonlinearities. The new system can demonstrate hyperchaotic, chaotic, quasi-periodic, and periodic behaviors for its different parameter values. All theoretical and numerical analysis are investigated to confirm the complex hyperchaotic behavior of our proposed model using many tools that include Kaplan-Yorke dimension, equilibrium points stability, bifurcation diagrams, and Lyapunov exponents. By means of Multisim software, the authors also designed an electronic circuit to confirm our proposed systems’ physical feasibility. MATLAB and Multisim simulation results excellently agree with each other, which More >

  • Open Access

    ARTICLE

    Deep Reinforcement Extreme Learning Machines for Secured Routing in Internet of Things (IoT) Applications

    K. Lavanya1,*, K. Vimala Devi2, B. R. Tapas Bapu3

    Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 837-848, 2022, DOI:10.32604/iasc.2022.023055 - 03 May 2022

    Abstract Multipath TCP (SMPTCP) has gained more attention as a valuable approach for IoT systems. SMPTCP is introduced as an evolution of Transmission Control Protocol (TCP) to pass packets simultaneously across several routes to completely exploit virtual networks on multi-homed consoles and other network services. The current multipath networking algorithms and simulation software strategies are confronted with sub-flow irregularity issues due to network heterogeneity, and routing configuration issues can be fixed adequately. To overcome the issues, this paper proposes a novel deep reinforcement-based extreme learning machines (DRLELM) approach to examine the complexities between routes, pathways, sub-flows, More >

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