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  • Open Access

    ARTICLE

    Healthcare Monitoring Using Ensemble Classifiers in Fog Computing Framework

    P. M. Arunkumar1, Mehedi Masud2, Sultan Aljahdali2, Mohamed Abouhawwash3,4,*

    Computer Systems Science and Engineering, Vol.45, No.2, pp. 2265-2280, 2023, DOI:10.32604/csse.2023.032571 - 03 November 2022

    Abstract Nowadays, the cloud environment faces numerous issues like synchronizing information before the switch over the data migration. The requirement for a centralized internet of things (IoT)-based system has been restricted to some extent. Due to low scalability on security considerations, the cloud seems uninteresting. Since healthcare networks demand computer operations on large amounts of data, the sensitivity of device latency evolved among health networks is a challenging issue. In comparison to cloud domains, the new paradigms of fog computing give fresh alternatives by bringing resources closer to users by providing low latency and energy-efficient data… More >

  • Open Access

    ARTICLE

    Phishing Websites Detection by Using Optimized Stacking Ensemble Model

    Zeyad Ghaleb Al-Mekhlafi1, Badiea Abdulkarem Mohammed1,2,*, Mohammed Al-Sarem3, Faisal Saeed3, Tawfik Al-Hadhrami4, Mohammad T. Alshammari1, Abdulrahman Alreshidi1, Talal Sarheed Alshammari1

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 109-125, 2022, DOI:10.32604/csse.2022.020414 - 08 October 2021

    Abstract Phishing attacks are security attacks that do not affect only individuals’ or organizations’ websites but may affect Internet of Things (IoT) devices and networks. IoT environment is an exposed environment for such attacks. Attackers may use thingbots software for the dispersal of hidden junk emails that are not noticed by users. Machine and deep learning and other methods were used to design detection methods for these attacks. However, there is still a need to enhance detection accuracy. Optimization of an ensemble classification method for phishing website (PW) detection is proposed in this study. A Genetic More >

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