Samir M. Umran^1,2, Songfeng Lu^1,3, Zaid Ameen Abduljabbar^1,4, Xueming Tang^1,*

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5389-5416, 2023, DOI:10.32604/cmc.2023.034331 - 28 December 2022

Abstract There are numerous internet-connected devices attached to the industrial process through recent communication technologies, which enable machine-to-machine communication and the sharing of sensitive data through a new technology called the industrial internet of things (IIoTs). Most of the suggested security mechanisms are vulnerable to several cybersecurity threats due to their reliance on cloud-based services, external trusted authorities, and centralized architectures; they have high computation and communication costs, low performance, and are exposed to a single authority of failure and bottleneck. Blockchain technology (BC) is widely adopted in the industrial sector for its valuable features in… More >

Kiran Jot Singh¹, Divneet Singh Kapoor^1,*, Mohamed Abouhawwash^2,3, Jehad F. Al-Amri⁴, Shubham Mahajan⁵, Amit Kant Pandit⁵

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 795-810, 2023, DOI:10.32604/iasc.2023.025177 - 06 June 2022

Abstract Navigation is an essential skill for robots. It becomes a cumbersome task for the robot in a human-populated environment, and Industry 5.0 is an emerging trend that focuses on the interaction between humans and robots. Robot behavior in a social setting is the key to human acceptance while ensuring human comfort and safety. With the advancement in robotics technology, the true use cases of robots in the tourism and hospitality industry are expanding in number. There are very few experimental studies focusing on how people perceive the navigation behavior of a delivery robot. A robotic… 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 >

Junwon Kim¹, Jiho Shin², Ki-Woong Park³, Jung Taek Seo^4,*

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5377-5394, 2022, DOI:10.32604/cmc.2022.026619 - 21 April 2022

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 >

R. Bhaskaran¹, R. Karuppathal¹, M. Karthick², J. Vijayalakshmi³, Seifedine Kadry⁴, Yunyoung Nam^5,*

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1593-1606, 2022, DOI:10.32604/iasc.2022.024902 - 24 March 2022

Abstract Industrial Internet of Things (IIoT) and Industry 4.0/5.0 offer several interconnections between machinery, equipment, processes, and personnel in diverse application areas namely logistics, supply chain, manufacturing, transportation, and healthcare. The conventional security-based solutions in IIoT environment get degraded due to the third parties. Therefore, the recent blockchain technology (BCT) can be employed to resolve trust issues and eliminate the need for third parties. Therefore, this paper presents a novel blockchain enabled secure optimal lightweight cryptography based image encryption (BC-LWCIE) technique for industry 4.0 environment. In addition, the BC-LWCIE technique involves the design of an optimal More >

Worakamol Wisetsri¹, Shamimul Qamar², Gaurav Verma^3,*, Deval Verma⁴, Varun Kumar Kakar⁵, Thanyanant Chansongpol⁶, Chanyanan Somtawinpongsai⁶, Chai Ching Tan⁷

Intelligent Automation & Soft Computing, Vol.33, No.3, pp. 1473-1483, 2022, DOI:10.32604/iasc.2022.024610 - 24 March 2022

Abstract Industry 4.0 is considered as the fourth revolution in industrial sector that represents the digitization of production process in a smarter way. Industry 4.0 refers to the intelligent networking of machines, their processes, and infrastructure, as well as the use of information and computer technology to transform industry. The technologies like industrial internet of things (IIoT), big data analytics, cloud computing, augmented reality and cyber security are the main pillars of industry 4.0. Industry 4.0, in particular, is strongly reliant on the IIoT that refers to the application of internet of things (IoT) in industrial… More >

Anwer Mustafa Hilal^1,*, Jaber S. Alzahrani², Ibrahim Abunadi³, Nadhem Nemri⁴, Fahd N. Al-Wesabi^5,6, Abdelwahed Motwakel¹, Ishfaq Yaseen¹, Abu Sarwar Zamani¹

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 333-348, 2022, DOI:10.32604/cmc.2022.024794 - 24 February 2022

Abstract In recent times, Industrial Internet of Things (IIoT) experiences a high risk of cyber attacks which needs to be resolved. Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks. Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network, the performance arrived at, in existing studies still needs improvement. In this scenario, the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT (PPBDL-IIoT) on 6G environment. The proposed PPBDL-IIoT technique aims… More >

Abdallah Abdallah¹, Ayman A. Aly², Bassem F. Felemban², Imran Khan³, Ki-Il Kim^4,*

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 157-179, 2022, DOI:10.32604/cmc.2022.023907 - 24 February 2022

Abstract The Internet of Things (IoT) has allowed for significant advancements in applications not only in the home, business, and environment, but also in factory automation. Industrial Internet of Things (IIoT) brings all of the benefits of the IoT to industrial contexts, allowing for a wide range of applications ranging from remote sensing and actuation to decentralization and autonomy. The expansion of the IoT has been set by serious security threats and obstacles, and one of the most pressing security concerns is the secure exchange of IoT data and fine-grained access control. A privacy-preserving multi-dimensional secure… More >

S. Gopalakrishnan^1,*, M. Senthil Kumaran²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1435-1449, 2022, DOI:10.32604/iasc.2022.020660 - 09 October 2021

Abstract In the automotive industry, multiple predictive maintenance units run behind the scenes in every production process to support significant product development, particularly among Accessories Manufacturers (AMs). As a result, they wish to maintain a positive relationship with vehicle manufacturers by providing 100 percent quality assurances for accessories. This is only achievable if they implement an effective anticipatory strategy that prioritizes quality control before and after product development. To do this, many sensors devices are interconnected in the production area to collect operational data (humanity, viscosity, and force) continuously received from machines and sent to backend… More >

Yinghua Zhang^1,2, Jian Liu¹, Yunfeng Peng¹, Yanfang Dong², Changming Zhao^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 239-257, 2020, DOI:10.32604/cmes.2020.010778 - 18 September 2020

Abstract Aiming for ultra-reliable low-latency wireless communications required in industrial internet of things (IIoT) applications, this paper studies a simple cognitive radio non-orthogonal multiple access (CR-NOMA) downlink system. This system consists of two secondary users (SUs) dynamically interfered by the primary user (PU), and its performance is characterized by the outage probability of the SU communications. This outage probability is calculated under two conditions where, a) the transmission of PU starts after the channel state information (CSI) is acquired, so the base station (BS) is oblivious of the interference, and b) when the BS is aware… More >