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  • Open Access

    ARTICLE

    A Security Operation and Event Management (SOEM) Platform for Critical Infrastructures Protection

    Roberto Caviglia1, Daniyar Aliaskharov2, Alessio Aceti1, Mila Dalla Preda3, Paola Girdinio2, Giovanni Battista Gaggero2,*

    CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5327-5340, 2025, DOI:10.32604/cmc.2025.068509 - 23 October 2025

    Abstract Industrial Control Systems (ICS) in Operational Technology (OT) environments face unique cybersecurity challenges due to legacy systems, critical operational needs, and incompatibility with standard IT security practices. To address these challenges, this paper presents the Security Operation and Event Management (SOEM) platform, a software designed to support Security Operations Centers (SOCs) in reaching full visibility of OT environments. SOEM integrates diverse log sources and intrusion detection systems, including logs generated by the control system itself and additional on-the-shelf products, to enhance situational awareness and enable rapid incident response. The pilot project was carried out within More >

  • Open Access

    ARTICLE

    Backdoor Malware Detection in Industrial IoT Using Machine Learning

    Maryam Mahsal Khan1, Attaullah Buriro2, Tahir Ahmad3,*, Subhan Ullah4

    CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4691-4705, 2024, DOI:10.32604/cmc.2024.057648 - 19 December 2024

    Abstract With the ever-increasing continuous adoption of Industrial Internet of Things (IoT) technologies, security concerns have grown exponentially, especially regarding securing critical infrastructures. This is primarily due to the potential for backdoors to provide unauthorized access, disrupt operations, and compromise sensitive data. Backdoors pose a significant threat to the integrity and security of Industrial IoT setups by exploiting vulnerabilities and bypassing standard authentication processes. Hence its detection becomes of paramount importance. This paper not only investigates the capabilities of Machine Learning (ML) models in identifying backdoor malware but also evaluates the impact of balancing the dataset More >

  • Open Access

    ARTICLE

    A Blockchain-Based Architecture for Enabling Cybersecurity in the Internet-of-Critical Infrastructures

    Mahmoud Ragab1,2,3,*, Ali Altalbe1

    CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1579-1592, 2022, DOI:10.32604/cmc.2022.025828 - 24 February 2022

    Abstract Due to the drastic increase in the number of critical infrastructures like nuclear plants, industrial control systems (ICS), transportation, it becomes highly vulnerable to several attacks. They become the major targets of cyberattacks due to the increase in number of interconnections with other networks. Several research works have focused on the design of intrusion detection systems (IDS) using machine learning (ML) and deep learning (DL) models. At the same time, Blockchain (BC) technology can be applied to improve the security level. In order to resolve the security issues that exist in the critical infrastructures and… More >

  • Open Access

    ARTICLE

    Cyber-security Risk Assessment Framework for Critical Infrastructures

    Zubair Baig1, Sherali Zeadally2

    Intelligent Automation & Soft Computing, Vol.25, No.1, pp. 121-129, 2019, DOI:10.31209/2018.100000049

    Abstract A critical infrastructure provides essential services to a nation’s population. Interruptions in its smooth operations are highly undesirable because they will cause significant and devastating consequences on all stakeholders in the society. In order to provide sustained protection to a nation’s critical infrastructure, we must continually assess and evaluate the risks thereof. We propose a risk assessment framework that can evaluate the risks posed to the security of a critical infrastructure from threat agents, with a special emphasis on the smart grid communications infrastructure. The framework defines finegrained risk identification to help quantify and assess More >

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