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  • Open Access


    Design Pattern and Challenges of Federated Learning with Applications in Industrial Control System

    Hina Batool1, Jiuyun Xu1,*, Ateeq Ur Rehman2, Habib Hamam3,4,5,6

    Journal on Artificial Intelligence, Vol.6, pp. 105-128, 2024, DOI:10.32604/jai.2024.049912

    Abstract Federated Learning (FL) appeared as an encouraging approach for handling decentralized data. Creating a FL system needs both machine learning (ML) knowledge and thinking about how to design system software. Researchers have focused a lot on the ML side of FL, but have not paid enough attention to designing the software architecture. So, in this survey, a set of design patterns is described to tackle the design issues. Design patterns are like reusable solutions for common problems that come up when designing software architecture. This paper focuses on (1) design patterns such as architectures, frameworks,… More >

  • Open Access


    Programmable Logic Controller Block Monitoring System for Memory Attack Defense in Industrial Control Systems

    Mingyu Lee1, Jiho Shin2, Jung Taek Seo3,*

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2427-2442, 2023, DOI:10.32604/cmc.2023.041774

    Abstract Cyberattacks targeting industrial control systems (ICS) are becoming more sophisticated and advanced than in the past. A programmable logic controller (PLC), a core component of ICS, controls and monitors sensors and actuators in the field. However, PLC has memory attack threats such as program injection and manipulation, which has long been a major target for attackers, and it is important to detect these attacks for ICS security. To detect PLC memory attacks, a security system is required to acquire and monitor PLC memory directly. In addition, the performance impact of the security system on the… More >

  • Open Access


    An Intelligent Approach for Intrusion Detection in Industrial Control System

    Adel Alkhalil1,*, Abdulaziz Aljaloud1, Diaa Uliyan1, Mohammed Altameemi1, Magdy Abdelrhman2,3, Yaser Altameemi4, Aakash Ahmad5, Romany Fouad Mansour6

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2049-2078, 2023, DOI:10.32604/cmc.2023.044506

    Abstract Supervisory control and data acquisition (SCADA) systems are computer systems that gather and analyze real-time data, distributed control systems are specially designed automated control system that consists of geographically distributed control elements, and other smaller control systems such as programmable logic controllers are industrial solid-state computers that monitor inputs and outputs and make logic-based decisions. In recent years, there has been a lot of focus on the security of industrial control systems. Due to the advancement in information technologies, the risk of cyberattacks on industrial control system has been drastically increased. Because they are so More >

  • Open Access


    Information Security Evaluation of Industrial Control Systems Using Probabilistic Linguistic MCDM Method

    Wenshu Xu, Mingwei Lin*

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 199-222, 2023, DOI:10.32604/cmc.2023.041475

    Abstract Industrial control systems (ICSs) are widely used in various fields, and the information security problems of ICSs are increasingly serious. The existing evaluation methods fail to describe the uncertain evaluation information and group evaluation information of experts. Thus, this paper introduces the probabilistic linguistic term sets (PLTSs) to model the evaluation information of experts. Meanwhile, we propose a probabilistic linguistic multi-criteria decision-making (PL-MCDM) method to solve the information security assessment problem of ICSs. Firstly, we propose a novel subscript equivalence distance measure of PLTSs to improve the existing methods. Secondly, we use the Best Worst… More >

  • Open Access


    RRCNN: Request Response-Based Convolutional Neural Network for ICS Network Traffic Anomaly Detection

    Yan Du1,2, Shibin Zhang1,2,*, Guogen Wan1,2, Daohua Zhou3, Jiazhong Lu1,2, Yuanyuan Huang1,2, Xiaoman Cheng4, Yi Zhang4, Peilin He5

    CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5743-5759, 2023, DOI:10.32604/cmc.2023.035919

    Abstract Nowadays, industrial control system (ICS) has begun to integrate with the Internet. While the Internet has brought convenience to ICS, it has also brought severe security concerns. Traditional ICS network traffic anomaly detection methods rely on statistical features manually extracted using the experience of network security experts. They are not aimed at the original network data, nor can they capture the potential characteristics of network packets. Therefore, the following improvements were made in this study: (1) A dataset that can be used to evaluate anomaly detection algorithms is produced, which provides raw network data. (2)… More >

  • Open Access


    A Novel Deep Learning Representation for Industrial Control System Data

    Bowen Zhang1,2,3, Yanbo Shi4, Jianming Zhao1,2,3,*, Tianyu Wang1,2,3, Kaidi Wang5

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2703-2717, 2023, DOI:10.32604/iasc.2023.033762

    Abstract Feature extraction plays an important role in constructing artificial intelligence (AI) models of industrial control systems (ICSs). Three challenges in this field are learning effective representation from high-dimensional features, data heterogeneity, and data noise due to the diversity of data dimensions, formats and noise of sensors, controllers and actuators. Hence, a novel unsupervised learning autoencoder model is proposed for ICS data in this paper. Although traditional methods only capture the linear correlations of ICS features, our deep industrial representation learning model (DIRL) based on a convolutional neural network can mine high-order features, thus solving the… More >

  • Open Access


    GRU-based Buzzer Ensemble for Abnormal Detection in Industrial Control Systems

    Hyo-Seok Kim1, Chang-Gyoon Lim2, Sang-Joon Lee3, Yong-Min Kim4,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1749-1763, 2023, DOI:10.32604/cmc.2023.026708

    Abstract Recently, Industrial Control Systems (ICSs) have been changing from a closed environment to an open environment because of the expansion of digital transformation, smart factories, and Industrial Internet of Things (IIoT). Since security accidents that occur in ICSs can cause national confusion and human casualties, research on detecting abnormalities by using normal operation data learning is being actively conducted. The single technique proposed by existing studies does not detect abnormalities well or provide satisfactory results. In this paper, we propose a GRU-based Buzzer Ensemble for Abnormal Detection (GBE-AD) model for detecting anomalies in industrial control… More >

  • Open Access


    Anomaly Detection for Industrial Internet of Things Cyberattacks

    Rehab Alanazi*, Ahamed Aljuhani

    Computer Systems Science and Engineering, Vol.44, No.3, pp. 2361-2378, 2023, DOI:10.32604/csse.2023.026712

    Abstract The evolution of the Internet of Things (IoT) has empowered modern industries with the capability to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational and financial harm to organizations. To preserve the confidentiality, integrity, and availability of IIoT networks, an anomaly-based intrusion detection system (IDS) can be used to provide secure, reliable, and efficient IIoT ecosystems. In this paper, we propose an anomaly-based IDS for IIoT networks as an effective security… More >

  • Open Access


    Anomaly Detection Framework in Fog-to-Things Communication for Industrial Internet of Things

    Tahani Alatawi*, Ahamed Aljuhani

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1067-1086, 2022, DOI:10.32604/cmc.2022.029283

    Abstract The rapid development of the Internet of Things (IoT) in the industrial domain has led to the new term the Industrial Internet of Things (IIoT). The IIoT includes several devices, applications, and services that connect the physical and virtual space in order to provide smart, cost-effective, and scalable systems. Although the IIoT has been deployed and integrated into a wide range of industrial control systems, preserving security and privacy of such a technology remains a big challenge. An anomaly-based Intrusion Detection System (IDS) can be an effective security solution for maintaining the confidentiality, integrity, and… More >

  • Open Access


    Improving Method of Anomaly Detection Performance for Industrial IoT Environment

    Junwon Kim1, Jiho Shin2, Ki-Woong Park3, Jung Taek Seo4,*

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5377-5394, 2022, DOI:10.32604/cmc.2022.026619

    Abstract Industrial Control System (ICS), which is based on Industrial IoT (IIoT), has an intelligent mobile environment that supports various mobility, but there is a limit to relying only on the physical security of the ICS environment. Due to various threat factors that can disrupt the workflow of the IIoT, machine learning-based anomaly detection technologies are being presented; it is also essential to study for increasing detection performance to minimize model errors for promoting stable ICS operation. In this paper, we established the requirements for improving the anomaly detection performance in the IIoT-based ICS environment by… More >

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