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Publications

Publication Date

Manuscript Submission Deadline

Feature Topic

Call for Papers

Recent developments in the field of Information and Communication Technology (ICT) have paved the way for smart digitalization everywhere. Critical infrastructures, ranging from hospitals to electricity grids, banking systems to water purification plants, thermal powerhouses to defense deterrence systems, are all connected online today. While this connectivity is undoubtedly improving all these services it is also posing complex security threats. These threats can have devastating effects on the services and their customers due to the sensitivity of the information carried over these cyber-physical systems. Recent cyberattacks on critical infrastructure have increased exponentially, thereby disrupting crucial operations, infringing sensitive business and personal information, and inflicting high costs on society. The severity, complexity, and frequency of cyberattacks on critical infrastructure are expected to increase further at a much faster pace in the near future. The reasons behind such an increasing number of cyberattacks are twofold. First, the underlying computing systems of critical infrastructure operate under dynamic environments where huge volumes of data are generated at high speed. In such scenarios, it is impossible to identify, detect, analyze, and defend against cyber threats in real-time. The conventional security solutions to critical infrastructure including Intrusion Detection System (IDS), Intrusion Prevention System (IPS) and access control mechanisms do not possess the capability to detect, prevent, and defend from the Advanced Persistent Threats (APTs) and novel zero-day attacks. Second, extracting insights from such huge and complex datasets for correct and timely decision-making have gone beyond human capabilities.

In this context, there is a pressing need to better understand the interplay between the latest advances in the domain of machine learning, artificial intelligence, deep learning, game theory, data science, and the area of critical-infrastructure security. This interplay is bound to create opportunities for research and innovation. The use of analytical tools based on machine learning, data mining, reinforcement learning and big data leads to timely detection and rapid reaction and response to cyberattacks through real-time analysis. Such a blend of technologies will significantly increase the degree of robustness and accuracy in protecting critical infrastructure systems.

This Feature Topic (FT) aims to explore novel and smart mechanisms to improve the detection and prevention of zero-day attacks, APTs, sophisticated malware variants and targeted cyberattacks for core underlying technologies used in critical infrastructure and cyber-physical systems. This forum brings together practitioners and researchers from all over the world to share their original contributions in the domain of Cybersecurity solutions for supervisory control and data acquisition systems. Prospective authors are invited to submit original and high-quality papers in any of the topics of interest which include, but are not limited to, the following:

  • Cyber-physical intelligent threats management
  • Supervisory control and data acquisition system security
  • Critical infrastructure cyberattacks prediction
  • Critical infrastructure network forensics
  • Smart cybersecurity operations center
  • Machine learning for proactive defense for critical infrastructure
  • Data analysis, feature extraction, detection of anomalies in cyber-physical system
  • Intelligent threat modeling for determining attack behavior
  • Big data analytics for cyber-physical systems
  • Game-theoretic reasoning in cyber-physical systems security
  • Cyber threat intelligence for Supervisory Control and Data Acquisition (SCADA) system
  • Profiling adversarial mechanisms and threat vectors for Industrial Control Systems (ICS)
  • Societal and legal aspects of cyber-physical systems

Submission Guidelines

Manuscripts should conform to the standard format as indicated in the Information for Authors section of the Manuscript Submission Guidelines. Please, check these guidelines carefully before submitting since submissions not complying with them will be administratively rejected without review.

All manuscripts to be considered for publication must be submitted by the deadline through Manuscript Central. Select the “February 2021/Cybersecurity” topic from the drop-down menu of Topic/Series titles. Please observe the dates specified here below noting that there will be no extension of submission deadline.

Important Dates

Manuscript Submission Deadline: 1 August 2020
Decision Notification: 1 November 2020
Final Manuscript Due: 15 December 2020
Publication Date: February 2021

Guest Editors

Haider Abbas
National University of Sciences and Technology, Pakistan (Lead)

Huimin Lu
Kyushu Institute of Technology, Japan

Rafia Inam
Ericsson, Sweden

Hafiz Malik
University of Michigan, USA