Rehab Alanazi^*, Ahamed Aljuhani

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2361-2378, 2023, DOI:10.32604/csse.2023.026712 - 01 August 2022

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 >

R. Gopi¹, R. Sheeba², K. Anguraj³, T. Chelladurai⁴, Haya Mesfer Alshahrani⁵, Nadhem Nemri^6,*, Tarek Lamoudan⁷

Computer Systems Science and Engineering, Vol.44, No.2, pp. 1567-1582, 2023, DOI:10.32604/csse.2023.025216 - 15 June 2022

Abstract Rapid increase in the large quantity of industrial data, Industry 4.0/5.0 poses several challenging issues such as heterogeneous data generation, data sensing and collection, real-time data processing, and high request arrival rates. The classical intrusion detection system (IDS) is not a practical solution to the Industry 4.0 environment owing to the resource limitations and complexity. To resolve these issues, this paper designs a new Chaotic Cuckoo Search Optimization Algorithm (CCSOA) with optimal wavelet kernel extreme learning machine (OWKELM) named CCSOA-OWKELM technique for IDS on the Industry 4.0 platform. The CCSOA-OWKELM technique focuses on the design… More >

Jiale Cheng¹, Zilong Jin^1,2,*

Journal on Internet of Things, Vol.4, No.3, pp. 183-195, 2022, DOI:10.32604/jiot.2022.042054 - 12 June 2023

Abstract A novel Federated learning classifier is proposed using the Dempster-Shafer (DS) theory for the set-valued classification of industrial IoT Distributed Denial of Service (DDoS) attack traffic. The proposed classifier, referred to as the evidence-based federated learning classifier, employs convolution and pooling layers to extract high-dimensional features of Distributed Denial of Service (DDoS) traffic from the local data of private industrial clients. The characteristics obtained from the various participants are transformed into mass functions and amalgamated utilizing Dempster’s rule within the DS layer, situated on the federated server. Lastly, the set value classification task of attack More >

Zeyong Sun¹, Guo Ran², Zilong Jin^1,3,*

Journal on Internet of Things, Vol.4, No.2, pp. 99-111, 2022, DOI:10.32604/jiot.2022.037416 - 28 March 2023

Abstract Intrusion detection is a hot field in the direction of network security. Classical intrusion detection systems are usually based on supervised machine learning models. These offline-trained models usually have better performance in the initial stages of system construction. However, due to the diversity and rapid development of intrusion techniques, the trained models are often difficult to detect new attacks. In addition, very little noisy data in the training process often has a considerable impact on the performance of the intrusion detection system. This paper proposes an intrusion detection system based on active incremental learning with… More >

Fahad F. Alruwaili^*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5809-5824, 2022, DOI:10.32604/cmc.2022.031613 - 28 July 2022

Abstract Internet of Things (IoT) is one of the hottest research topics in recent years, thanks to its dynamic working mechanism that integrates physical and digital world into a single system. IoT technology, applied in industries, is termed as Industrial IoT (IIoT). IIoT has been found to be highly susceptible to attacks from adversaries, based on the difficulties observed in IIoT and its increased dependency upon internet and communication network. Intentional or accidental attacks on these approaches result in catastrophic effects like power outage, denial of vital health services, disruption to civil service, etc., Thus, there… More >

Yinghua Zhang^1,*, Rui Cao¹, Lixin Tian¹, Rong Dai², Zhennan Cao², Jim Feng³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6513-6534, 2022, DOI:10.32604/cmc.2022.029467 - 28 July 2022

Abstract With the continuous maturity of the fifth generation (5G) communications, industrial Internet of Things (IIoT) technology has been widely applied in fields such as smart factories. In smart factories, 5G-based production line monitoring can improve production efficiency and reduce costs, but there are problems with limited monitoring coverage and insufficient wireless spectrum resources, which restricts the application of IIoT in the construction of smart factories. In response to these problems, we propose a hybrid spectrum access mechanism based on Non-Orthogonal Multiple Access (NOMA) cooperative relaying transmission to improve the monitoring coverage and spectrum efficiency. As… More >

Tahani Alatawi^*, Ahamed Aljuhani

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1067-1086, 2022, DOI:10.32604/cmc.2022.029283 - 18 May 2022

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 >

Wenjun Li¹, Siyang Zhang¹, Guangwei Wu², Aldosary Saad³, Amr Tolba^3,4, Gwang-jun Kim^5,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 4215-4231, 2022, DOI:10.32604/cmc.2022.024204 - 21 April 2022

Abstract Recently, the development of Industrial Internet of Things has taken the advantage of 5G network to be more powerful and more intelligent. However, the upgrading of 5G network will cause a variety of issues increase, one of them is the increased cost of coverage. In this paper, we propose a sustainable wireless sensor networks system, which avoids the problems brought by 5G network system to some extent. In this system, deploying relays and selecting routing are for the sake of communication and charging. The main aim is to minimize the total energy-cost of communication under More >

Radwa Marzouk¹, Fadwa Alrowais², Noha Negm³, Mimouna Abdullah Alkhonaini⁴, Manar Ahmed Hamza^5,*, Mohammed Rizwanullah⁵, Ishfaq Yaseen⁵, Abdelwahed Motwakel⁵

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3763-3775, 2022, DOI:10.32604/cmc.2022.027483 - 29 March 2022

Abstract Industrial Internet of Things (IIoT) is an emerging field which connects digital equipment as well as services to physical systems. Intrusion detection systems (IDS) can be designed to protect the system from intrusions or attacks. In this view, this paper presents a novel hybrid deep learning with metaheuristics enabled intrusion detection (HDL-MEID) technique for clustered IIoT environments. The HDL-MEID model mainly intends to organize the IIoT devices into clusters and enabled secure communication. Primarily, the HDL-MEID technique designs a new chaotic mayfly optimization (CMFO) based clustering approach for the effective choice of the Cluster Heads More >

Alaa Omran Almagrabi^*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3961-3983, 2022, DOI:10.32604/cmc.2022.026513 - 29 March 2022

Abstract The Industrial Internet of Things (IIoT) has been growing for presentations in industry in recent years. Security for the IIoT has unavoidably become a problem in terms of creating safe applications. Due to continual needs for new functionality, such as foresight, the number of linked devices in the industrial environment increases. Certification of fewer signatories gives strong authentication solutions and prevents trustworthy third parties from being publicly certified among available encryption instruments. Hence this blockchain-based endpoint protection platform (BCEPP) has been proposed to validate the network policies and reduce overall latency in isolation or hold… More >