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  • Open Access

    ARTICLE

    GMLP-IDS: A Novel Deep Learning-Based Intrusion Detection System for Smart Agriculture

    Abdelwahed Berguiga1,2,*, Ahlem Harchay1,2, Ayman Massaoudi1,2, Mossaad Ben Ayed3, Hafedh Belmabrouk4

    CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 379-402, 2023, DOI:10.32604/cmc.2023.041667

    Abstract Smart Agriculture, also known as Agricultural 5.0, is expected to be an integral part of our human lives to reduce the cost of agricultural inputs, increasing productivity and improving the quality of the final product. Indeed, the safety and ongoing maintenance of Smart Agriculture from cyber-attacks are vitally important. To provide more comprehensive protection against potential cyber-attacks, this paper proposes a new deep learning-based intrusion detection system for securing Smart Agriculture. The proposed Intrusion Detection System IDS, namely GMLP-IDS, combines the feedforward neural network Multilayer Perceptron (MLP) and the Gaussian Mixture Model (GMM) that can better protect the Smart Agriculture… More >

  • Open Access

    ARTICLE

    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 Method (BWM) method and Criteria… More >

  • Open Access

    ARTICLE

    AI-Driven FBMC-OQAM Signal Recognition via Transform Channel Convolution Strategy

    Zeliang An1, Tianqi Zhang1,*, Debang Liu1, Yuqing Xu2, Gert Frølund Pedersen2, Ming Shen2

    CMC-Computers, Materials & Continua, Vol.76, No.3, pp. 2817-2834, 2023, DOI:10.32604/cmc.2023.037832

    Abstract With the advent of the Industry 5.0 era, the Internet of Things (IoT) devices face unprecedented proliferation, requiring higher communications rates and lower transmission delays. Considering its high spectrum efficiency, the promising filter bank multicarrier (FBMC) technique using offset quadrature amplitude modulation (OQAM) has been applied to Beyond 5G (B5G) industry IoT networks. However, due to the broadcasting nature of wireless channels, the FBMC-OQAM industry IoT network is inevitably vulnerable to adversary attacks from malicious IoT nodes. The FBMC-OQAM industry cognitive radio network (ICRNet) is proposed to ensure security at the physical layer to tackle the above challenge. As a… More >

  • Open Access

    ARTICLE

    An Efficient and Provably Secure SM2 Key-Insulated Signature Scheme for Industrial Internet of Things

    Senshan Ouyang1,2, Xiang Liu2, Lei Liu2, Shangchao Wang2, Baichuan Shao3, Yang Zhao3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 903-915, 2024, DOI:10.32604/cmes.2023.028895

    Abstract With the continuous expansion of the Industrial Internet of Things (IIoT), more and more organisations are placing large amounts of data in the cloud to reduce overheads. However, the channel between cloud servers and smart equipment is not trustworthy, so the issue of data authenticity needs to be addressed. The SM2 digital signature algorithm can provide an authentication mechanism for data to solve such problems. Unfortunately, it still suffers from the problem of key exposure. In order to address this concern, this study first introduces a key-insulated scheme, SM2-KI-SIGN, based on the SM2 algorithm. This scheme boasts strong key insulation… More >

  • Open Access

    REVIEW

    Comprehensive Survey of the Landscape of Digital Twin Technologies and Their Diverse Applications

    Haiyu Chen1, Haijian Shao1,2,*, Xing Deng1, Lijuan Wang1, Xia Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 125-165, 2024, DOI:10.32604/cmes.2023.027834

    Abstract The concept of the digital twin, also known colloquially as the DT, is a fundamental principle within Industry 4.0 framework. In recent years, the concept of digital siblings has generated considerable academic and practical interest. However, academia and industry have used a variety of interpretations, and the scientific literature lacks a unified and consistent definition of this term. The purpose of this study is to systematically examine the definitional landscape of the digital twin concept as outlined in scholarly literature, beginning with its origins in the aerospace domain and extending to its contemporary interpretations in the manufacturing industry. Notably, this… More >

  • Open Access

    ARTICLE

    State Accurate Representation and Performance Prediction Algorithm Optimization for Industrial Equipment Based on Digital Twin

    Ying Bai1,*, Xiaoti Ren2, Hong Li1

    Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2999-3018, 2023, DOI:10.32604/iasc.2023.040124

    Abstract The combination of the Industrial Internet of Things (IIoT) and digital twin (DT) technology makes it possible for the DT model to realize the dynamic perception of equipment status and performance. However, conventional digital modeling is weak in the fusion and adjustment ability between virtual and real information. The performance prediction based on experience greatly reduces the inclusiveness and accuracy of the model. In this paper, a DT-IIoT optimization model is proposed to improve the real-time representation and prediction ability of the key equipment state. Firstly, a global real-time feedback and the dynamic adjustment mechanism is established by combining DT-IIoT… More >

  • Open Access

    ARTICLE

    AID4I: An Intrusion Detection Framework for Industrial Internet of Things Using Automated Machine Learning

    Anıl Sezgin1,2,*, Aytuğ Boyacı3

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2121-2143, 2023, DOI:10.32604/cmc.2023.040287

    Abstract By identifying and responding to any malicious behavior that could endanger the system, the Intrusion Detection System (IDS) is crucial for preserving the security of the Industrial Internet of Things (IIoT) network. The benefit of anomaly-based IDS is that they are able to recognize zero-day attacks due to the fact that they do not rely on a signature database to identify abnormal activity. In order to improve control over datasets and the process, this study proposes using an automated machine learning (AutoML) technique to automate the machine learning processes for IDS. Our ground-breaking architecture, known as AID4I, makes use of… More >

  • Open Access

    PROCEEDINGS

    A Review of Differential Form Meshfree Methods for Industrial Applications

    Félix R. Saucedo Zendejo1,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023. 09622

    Abstract This report documents the application and development of differential form meshfree methods for the numerical simulation and modeling in engineering applied problems. Some of the features of this family of methods include its good numerical stability, the ease boundary condition incorporation, the approximation of the governing equations directly in the nodes that discretize the domain and the ease with which they can be numerically implemented [1-2]. Moreover, their meshless nature gives them the advantage of dealing with fragmentation and highly distorted domains without the use of computational expensive remeshing approaches. All these characteristics have promoted its application in different industrial… More >

  • Open Access

    PROCEEDINGS

    Efficient Computational Inverse Method for Positioning Accuracy Estimation of Industrial Robot Under Stochastic Uncertainties

    Jinhe Zhang2, Jie Liu1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.09279

    Abstract The small uncertainties of geometric parameters of industrial robot, which are caused by links manufacturing and service wear errors, can deteriorate the positioning accuracy of end-effector through multi-level propagation and is difficult to be measured and compensated by high-precision instruments. Hence, an efficient inverse identification method of parameter uncertainty based on global sensitivity analysis and optimal measurement point selection is proposed. In order to ensure the universality of identification results in calibration and control works, the standard Denavit-Hartenberg (D-H) method is employed to establish the kinematic model of series 6 degrees of freedom (DOF) robots. Considering the stochastic error between… More >

  • Open Access

    ARTICLE

    Edge Cloud Selection in Mobile Edge Computing (MEC)-Aided Applications for Industrial Internet of Things (IIoT) Services

    Dae-Young Kim1, SoYeon Lee2, MinSeung Kim2, Seokhoon Kim1,*

    Computer Systems Science and Engineering, Vol.47, No.2, pp. 2049-2060, 2023, DOI:10.32604/csse.2023.040473

    Abstract In many IIoT architectures, various devices connect to the edge cloud via gateway systems. For data processing, numerous data are delivered to the edge cloud. Delivering data to an appropriate edge cloud is critical to improve IIoT service efficiency. There are two types of costs for this kind of IoT network: a communication cost and a computing cost. For service efficiency, the communication cost of data transmission should be minimized, and the computing cost in the edge cloud should be also minimized. Therefore, in this paper, the communication cost for data transmission is defined as the delay factor, and the… More >

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