Digital Twins and Cyber-Physical Systems towards Cybersecurity and Smart Manufacturing
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 31 January 2025 | Viewed by 61
Special Issue Editors
Interests: virtual commissioning; robotics; simulation; digital twin; pneumatics; hydraulics
Interests: Internet of Things (IoT); neural networks
Interests: cybersecurity; digital forensics; cyberawareness; information security; cyber situational awareness; computer networking security; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue serves as a guide for potential authors, clarifying the background and objectives of our focus on Digital Twins (DTs) and Cyber-Physical Systems (CPSs) in enhancing cybersecurity and smart manufacturing, including industrial robotics and mechatronics. Digital Twins, as sophisticated virtual models of physical systems, revolutionize manufacturing by enabling real-time monitoring, simulation, and optimization. Integrated with CPSs, these models facilitate seamless interaction between computational elements and physical processes, driving innovations in smart manufacturing.
A major focus is on industrial cybersecurity. As IoT and smart devices proliferate in manufacturing, safeguarding these interconnected systems from cyber threats is critical. We invite research contributions on securing DT and CPS frameworks, emphasizing novel strategies to protect data integrity and operational continuity.
Topics of interest include:
- Fundamentals of DTs and CPSs in smart manufacturing and industrial robotics.
- Integrating sensors, data analytics, and AI in DTs and CPSs for smart manufacturing and mechatronics.
- Practical implementation and validation of DTs and CPSs for cybersecurity in manufacturing and robotics.
- Future applications of DTs and CPSs in cybersecurity, smart manufacturing, and mechatronics.
- Novel security strategies for DT and CPS frameworks.
- Other relevant topics related to DTs, CPSs, cybersecurity, and smart manufacturing.
This issue provides a platform to exchange ideas and showcase research that enhances manufacturing efficiency, adaptability, and cybersecurity.
Dr. Roman Ružarovský
Dr. Tibor Horak
Prof. Dr. Mario Antunes
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. Applied Sciences 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
- digital twins
- cyber–physical systems
- cybersecurity
- smart manufacturing
- industrial robotics
- mechatronics
- IoT
- data analytics
- artificial intelligence
- predictive maintenance
