Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.3
2.6
Journals
Electronics
Special Issues
Cyber-Physical Systems in Industrial IoT
share announcement

Cyber-Physical Systems in Industrial IoT

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Industrial Electronics".

Deadline for manuscript submissions: 15 October 2024 | Viewed by 10637

Special Issue Editors

Prof. Dr. Li Da Xu

grade E-Mail Website
Guest Editor
Department of Information Technology, Old Dominion University, Norfolk, VA 23529, USA
Interests: industrial information integration engineering; industrial information systems; industrial informatics; enterprise systems
Special Issues, Collections and Topics in MDPI journals
Dr. Shancang Li

E-Mail Website
Guest Editor
Department of Computer Science and Creative Technologies, University of the West of England, Coldharbour Ln, Bristol BS16 1QY, UK
Interests: cyber security; digital forensics; internet of things; network security

Special Issue Information

Dear Colleagues,

In general, a commonly accepted definition of cyber-physical systems (CPSs) refers to systems where software and hardware components are seamlessly integrated toward performing well-defined tasks.

CPSs are one of the core technologies of Industry 4.0. The integration of CPSs is essential in Industry 4.0 functioning. With CPSs, machines are able to communicate with each other, and decentralized control systems are able to optimize production. The integration of CPSs is leading to complexities emerging from the interactions among cyber systems and the uncertain dynamic behavior of physical systems. In recent years, CPSs have become increasingly interconnected and more deeply intertwined as they interact with each other in a myriad of ways. The integration of constituent systems in CPSs is a challenge. A suitable systems theory concerning the interconnection and interactions of cyber and physical systems as a whole is needed, and larger contexts need to be made explicit.

CPSs are increasingly interconnected with a meta-system such as the Industry 4.0 ecological environment, and their behavior depends on interactions with other systems components. Numerous interactions of different characteristics may be involved, such as interactions within a system or a subsystem, interactions between systems and/or subsystems, and interactions between a system and its environment. Such interrelated subsystems are capable of dynamic change. Interactions can occur between interactions as well, and some interactions only emerge when the system as a whole is considered. Industry 4.0 technologies are currently amplifying such interactions. If Industry 4.0 is to be employed successfully, these interactions must be understood and the methods for designing and implementing Industry 4.0 technologies must account for such interactions. Currently, these complex interactions are not being heavily investigated. One of the challenges we face is making use of cutting-edge ICT as well as systems science and engineering techniques to understand such complex interactions.

This Special Issue will focus on (but is not limited to) the following topics:

- New computing architecture for CPSs in industrial IoT;

- New communication mechanisms for CPSs in industrial IoT;

- Advanced AI/ML models for CPSs in industrial IoT;

- Advanced networking among CPSs for industrial IoT;

- Applications of CPSs in industrial IoT.

Prof. Dr. Li Da Xu
Dr. Shancang Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cyber-physical systems (CPSs)
  • IoT
  • industrial IoT

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

19 pages, 3465 KiB  
Article
Design and Implementation of Lightweight Certificateless Secure Communication Scheme on Industrial NFV-Based IPv6 Virtual Networks
by Zeeshan Ashraf, Adnan Sohail and Muddesar Iqbal
Electronics 2024, 13(13), 2649; https://doi.org/10.3390/electronics13132649 - 5 Jul 2024
Viewed by 1012
Abstract
With the fast growth of the Industrial Internet of Everything (IIoE), computing and telecommunication industries all over the world are moving rapidly towards the IPv6 address architecture, which supports virtualization architectures such as Network Function Virtualization (NFV). NFV provides networking services like routing, [...] Read more.
With the fast growth of the Industrial Internet of Everything (IIoE), computing and telecommunication industries all over the world are moving rapidly towards the IPv6 address architecture, which supports virtualization architectures such as Network Function Virtualization (NFV). NFV provides networking services like routing, security, storage, etc., through software-based virtual machines. As a result, NFV reduces equipment costs. Due to the increase in applications on Industrial Internet of Things (IoT)-based networks, security threats have also increased. The communication links between people and people or from one machine to another machine are insecure. Usually, critical data are exchanged over the IoE, so authentication and confidentiality are significant concerns. Asymmetric key cryptosystems increase computation and communication overheads. This paper proposes a lightweight and certificateless end-to-end secure communication scheme to provide security services against replay attacks, man-in-the-middle (MITM) attacks, and impersonation attacks with low computation and communication overheads. The system is implemented on Linux-based Lubuntu 20.04 virtual machines using Java programming connected to NFV-based large-scale hybrid IPv4-IPv6 virtual networks. Finally, we compare the performance of our proposed security scheme with existing schemes based on the computation and communication costs. In addition, we measure and analyze the performance of our proposed secure communication scheme over NFV-based virtualized networks with regard to several parameters like end-to-end delay and packet loss. The results of our comparison with existing security schemes show that our proposed security scheme reduces the computation cost by 38.87% and the communication cost by 26.08%. Full article
(This article belongs to the Special Issue Cyber-Physical Systems in Industrial IoT)
►▼ Show Figures

Figure 1

14 pages, 1000 KiB  
Article
Enhancing Communication in CPS Using Graph-Based Reply Relationship Identification in Multi-Party Conversations
by Bingwei Zhu, Jinzhu Yang, Lirong Qiu, Weichun Sun and Bin Hou
Electronics 2024, 13(12), 2302; https://doi.org/10.3390/electronics13122302 - 12 Jun 2024
Viewed by 580
Abstract
To enhance communication and collaborative work efficiency in cyber–physical systems (CPSs) within the Industry 4.0 environment, this study investigates a graph-based machine learning approach aimed at optimizing information interaction during multi-party conversations. Devices within CPSs must efficiently exchange information in real time to [...] Read more.
To enhance communication and collaborative work efficiency in cyber–physical systems (CPSs) within the Industry 4.0 environment, this study investigates a graph-based machine learning approach aimed at optimizing information interaction during multi-party conversations. Devices within CPSs must efficiently exchange information in real time to synchronize operations and responses. This research treats these interactions as intricate graph structures and uses graph learning techniques to accurately identify communication links and dependencies among devices. This improvement leads to more accurate decision-making and smoother operations. Our methodology involves a real-time analysis of structural patterns and node attributes within conversations, improving information flow and comprehension. The empirical findings demonstrate that this approach significantly enhances production efficiency, system adaptability, and minimizes delays attributed to communication misunderstandings. Our method can effectively identify the communication relationships between devices, significantly improving the efficiency and accuracy of information transmission. This improved communication capability leads to an enhanced production efficiency of the entire system. Full article
(This article belongs to the Special Issue Cyber-Physical Systems in Industrial IoT)
►▼ Show Figures

Figure 1

11 pages, 2249 KiB  
Article
Attention-Mechanism-Based Face Feature Extraction Model for WeChat Applet on Mobile Devices
by Jianyu Xiao, Hongyang Zhou, Qigong Lei, Huanhua Liu, Zunlong Xiao and Shenxi Huang
Electronics 2024, 13(1), 201; https://doi.org/10.3390/electronics13010201 - 2 Jan 2024
Viewed by 1692
Abstract
Face recognition technology has been widely used with the WeChat applet on mobile devices; however, facial images are captured on mobile devices and then transmitted to a server for feature extraction and recognition in most existing systems. There are significant security risks related [...] Read more.
Face recognition technology has been widely used with the WeChat applet on mobile devices; however, facial images are captured on mobile devices and then transmitted to a server for feature extraction and recognition in most existing systems. There are significant security risks related to personal information leakage with these transmissions. Therefore, we propose a face recognition framework for the WeChat applet in which face features are extracted in WeChat by the proposed Face Feature Extraction Model based on Attention Mechanism (FFEM-AM), and only the extracted features are transmitted to the server for recognition. In order to balance the prediction accuracy and model complexity, the structure of the proposed FFEM-AM is lightweight, and Efficient Channel Attention (ECA) was introduced to improve the prediction accuracy. The proposed FFEM-AM was evaluated using a self-built database and the WeChat applet on mobile devices. The experiments show that the prediction accuracy of the proposed FFEM-AM was 98.1%, the running time was less than 100 ms, and the memory cost was only 6.5 MB. Therefore, this demonstrates that the proposed FFEM-AM has high prediction accuracy and can also be deployed with the WeChat applet. Full article
(This article belongs to the Special Issue Cyber-Physical Systems in Industrial IoT)
►▼ Show Figures

Figure 1

24 pages, 696 KiB  
Article
Machine-Learning-Based Vulnerability Detection and Classification in Internet of Things Device Security
by Sarah Bin Hulayyil, Shancang Li and Lida Xu
Electronics 2023, 12(18), 3927; https://doi.org/10.3390/electronics12183927 - 18 Sep 2023
Cited by 7 | Viewed by 6654
Abstract
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and [...] Read more.
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in IoT environments, and a review of recent research trends is presented. Full article
(This article belongs to the Special Issue Cyber-Physical Systems in Industrial IoT)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-4
Back to TopTop