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IJIS Special Issue 2024 : Reinforcing Cyber Security of Critical Infrastructures through Digital Twins

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Link: https://link.springer.com/collections/jeddaggegb
 
When N/A
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Submission Deadline Oct 31, 2024
Categories    critical infrastructures   cyber-attacks   cyber security   digital twins
 

Call For Papers

IJIS Special Issue: Reinforcing Cyber Security of Critical Infrastructures through Digital Twins

Digital Twins are seen as one of the emerging technologies. In recent years, the conceptualization, development, and implementation of digital twins in different domains is clearly evident. There will be more and more connected devices in use around the world with the evolution of technologies like the Internet of Things. Furthermore, with the emergence of remote access, operators and critical systems are increasingly connected using remote connectivity. At the same time, there is an increased rate of cyber-attacks. These are reasons why cyber security is critically important to contemporary society as these factors make critical infrastructures even more susceptible to cyber-attacks. However, in order to make critical infrastructures cyber-resilient, performing cyber security testing/exercises on real-world systems is impractical. Digital twins in different domains provide the capability to be used for a wide range of cyber security tests. On the other hand, digital twins are susceptible to different types of cyber threats that could lead to negative consequences.

This special issue aims to gather high-quality empirical, experimental, and theoretical research reporting original and unpublished results.

Digital Twins research relates to multiple United Nations Sustainable Development Goals (SDGs) through advances in cybersecurity, health care, data management, and education, among other fields. This collection particularly welcomes submissions related to SDG 9 “Industry, Innovation, and Infrastructure.”

Topics of interest for this special issue include, but are not limited to:

• Methods and techniques in the development of digital twins for cyber security

• Artificial intelligence and machine learning approaches for digital twins

• Enabling technologies for digital twins

• Digital twins for security testing

• Use of digital twins in the security operations center

• Cyber situational awareness through digital twins

• Digital twins for attack prediction

• Digital twins in cyber risk management

• Digital twin-based anomaly detection

• Digital twins for decision making in cyber security

• Incident response using digital twins

• Cyber security training/education via digital twins

• Secure data management in digital twins

• Human digital twin for cyber security

• Cyber security threats in adopting digital twins

• Security issues in Condition Monitoring, diagnostics, and prognosis in digital twins

• Novel solutions for securing critical components with digital twins.

Submitted papers should present original, unpublished work, relevant to one of the topics of the Special Issue. All submitted papers will be evaluated on the basis of relevance, significance of contribution, technical quality, scholarship, and quality of presentation, by at least two independent reviewers. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review at another journal or conference at any time during the review process.

Schedule

Submission Deadline: 31st October 2024

First Round of Review Notification: Rolling Basis

Revised Paper Submission: Rolling Basis

Final Decision Notification: Rolling Basis

Planned Publication: 2025

Editors

Sabarathinam Chockalingam, Department of Risk and Security, Institute for Energy Technology (IFE), Halden, Norway; sabarathinam.chockalingam@ife.no

Vasileios Gkioulos, Department of Information Security and Communication Technology, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU); vasileios.gkioulos@ntnu.no

Clara Maathuis, Department of Computer Science, Open University of the Netherlands, Heerlen, The Netherlands; clara.maathuis@ou.nl

Sanjay Misra​​, Department of Applied Data Science, Institute for Energy Technology (IFE), Halden, Norway; sanjay.misra@ife.no

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