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  • Open Access

    ARTICLE

    Industrial Datasets with ICS Testbed and Attack Detection Using Machine Learning Techniques

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Asaad Balla1, Mohammad Tahir2, Elfatih A. A. Elsheikh3, F. M. Suliman3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1345-1360, 2022, DOI:10.32604/iasc.2022.020801

    Abstract Industrial control systems (ICS) are the backbone for the implementation of cybersecurity solutions. They are susceptible to various attacks, due to openness in connectivity, unauthorized attempts, malicious attacks, use of more commercial off the shelf (COTS) software and hardware, and implementation of Internet protocols (IP) that exposes them to the outside world. Cybersecurity solutions for Information technology (IT) secured with firewalls, intrusion detection/protection systems do nothing much for Operational technology (OT) ICS. An innovative concept of using real operational technology network traffic-based testbed, for cyber-physical system simulation and analysis, is presented. The testbed is equipped with real-time attacks using in-house… More >

  • Open Access

    ARTICLE

    Development and Application of a Heating Remote Monitoring System Based on KingSCADA

    Chunlei Liu, Tian Gao, Chen Wang, Peiqi Wang, Limin Wang, Yi Wang, Yong Sun*

    FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.6, pp. 1179-1193, 2021, DOI:10.32604/fdmp.2021.017543

    Abstract A remote monitoring system for a secondary heating pipe network is designed on the basis of the KingSCADA software. Remote data communication is implemented through the IP mapping technology. Remote data are sorted through IOServer, and the remote monitoring of the pipe network unit port return is implemented accordingly. Using data such as water temperature and pressure of the water supply and return pipes, valve opening can be remotely adjusted to optimize the performances of the network to meet user needs in real time. The research results show that this remote monitoring system displays a reasonable degree of stability and… More >

  • Open Access

    Management of Schemes and Threat Prevention in ICS Partner Companies Security

    Sangdo Lee1, Jun-Ho Huh2,*

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3659-3684, 2021, DOI:10.32604/cmc.2021.015632

    Abstract An analysis of the recent major security incidents related to industrial control systems, revealed that most had been caused by company employees. Therefore, enterprise security management systems have been developed to focus on companies’ personnel. Nonetheless, several hacking incidents, involving major companies and public/financial institutions, were actually attempted by the cooperative firms or the outsourced manpower undertaking maintenance work. Specifically, institutions that operate industrial control systems (ICSs) associated with critical national infrastructures, such as traffic or energy, have contracted several cooperative firms. Nonetheless, ICT's importance is gradually increasing, due to outsourcing, and is the most vulnerable factor in security. This… More >

  • Open Access

    ARTICLE

    Power Data Preprocessing Method of Mountain Wind Farm Based on POT-DBSCAN

    Anfeng Zhu, Zhao Xiao, Qiancheng Zhao*

    Energy Engineering, Vol.118, No.3, pp. 549-563, 2021, DOI:10.32604/EE.2021.014177

    Abstract Due to the frequent changes of wind speed and wind direction, the accuracy of wind turbine (WT) power prediction using traditional data preprocessing method is low. This paper proposes a data preprocessing method which combines POT with DBSCAN (POT-DBSCAN) to improve the prediction efficiency of wind power prediction model. Firstly, according to the data of WT in the normal operation condition, the power prediction model of WT is established based on the Particle Swarm Optimization (PSO) Arithmetic which is combined with the BP Neural Network (PSO-BP). Secondly, the wind-power data obtained from the supervisory control and data acquisition (SCADA) system… More >

  • Open Access

    ARTICLE

    Anomaly Detection in ICS Datasets with Machine Learning Algorithms

    Sinil Mubarak1, Mohamed Hadi Habaebi1,*, Md Rafiqul Islam1, Farah Diyana Abdul Rahman, Mohammad Tahir2

    Computer Systems Science and Engineering, Vol.37, No.1, pp. 33-46, 2021, DOI:10.32604/csse.2021.014384

    Abstract An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as… More >

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