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  • Open Access

    ARTICLE

    A Probabilistic Trust Model and Control Algorithm to Protect 6G Networks against Malicious Data Injection Attacks in Edge Computing Environments

    Borja Bordel Sánchez1,*, Ramón Alcarria2, Tomás Robles1

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 631-654, 2024, DOI:10.32604/cmes.2024.050349

    Abstract Future 6G communications are envisioned to enable a large catalogue of pioneering applications. These will range from networked Cyber-Physical Systems to edge computing devices, establishing real-time feedback control loops critical for managing Industry 5.0 deployments, digital agriculture systems, and essential infrastructures. The provision of extensive machine-type communications through 6G will render many of these innovative systems autonomous and unsupervised. While full automation will enhance industrial efficiency significantly, it concurrently introduces new cyber risks and vulnerabilities. In particular, unattended systems are highly susceptible to trust issues: malicious nodes and false information can be easily introduced into… More >

  • Open Access

    ARTICLE

    Flower Pollination Heuristics for Nonlinear Active Noise Control Systems

    Wasim Ullah Khan1,*, Yigang He1, Muhammad Asif Zahoor Raja2, Naveed Ishtiaq Chaudhary3, Zeshan Aslam Khan3, Syed Muslim Shah4

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 815-834, 2021, DOI:10.32604/cmc.2021.014674

    Abstract Abstract In this paper, a novel design of the flower pollination algorithm is presented for model identification problems in nonlinear active noise control systems. The recently introduced flower pollination based heuristics is implemented to minimize the mean squared error based merit/cost function representing the scenarios of active noise control system with linear/nonlinear and primary/secondary paths based on the sinusoidal signal, random and complex random signals as noise interferences. The flower pollination heuristics based active noise controllers are formulated through exploitation of nonlinear filtering with Volterra series. The comparative study on statistical observations in terms of… More >

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