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  • Open Access

    ARTICLE

    The Effect of Key Nodes on the Malware Dynamics in the Industrial Control Network

    Qiang Fu1, Jun Wang1,*, Changfu Si1, Jiawei Liu2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 329-349, 2024, DOI:10.32604/cmc.2024.048117

    Abstract As industrialization and informatization become more deeply intertwined, industrial control networks have entered an era of intelligence. The connection between industrial control networks and the external internet is becoming increasingly close, which leads to frequent security accidents. This paper proposes a model for the industrial control network. It includes a malware containment strategy that integrates intrusion detection, quarantine, and monitoring. Based on this model, the role of key nodes in the spread of malware is studied, a comparison experiment is conducted to validate the impact of the containment strategy. In addition, the dynamic behavior of the model is analyzed, the… More >

  • Open Access

    ARTICLE

    A New Intrusion Detection Algorithm AE-3WD for Industrial Control Network

    Yongzhong Li1,2,*, Cong Li1, Yuheng Li3, Shipeng Zhang2

    Journal of New Media, Vol.4, No.4, pp. 205-217, 2022, DOI:10.32604/jnm.2022.034778

    Abstract In this paper, we propose a intrusion detection algorithm based on auto-encoder and three-way decisions (AE-3WD) for industrial control networks, aiming at the security problem of industrial control network. The ideology of deep learning is similar to the idea of intrusion detection. Deep learning is a kind of intelligent algorithm and has the ability of automatically learning. It uses self-learning to enhance the experience and dynamic classification capabilities. We use deep learning to improve the intrusion detection rate and reduce the false alarm rate through learning, a denoising AutoEncoder and three-way decisions intrusion detection method AE-3WD is proposed to improve… More >

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