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Computers
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Using New Technologies in Cyber Security Solutions (3rd Edition)
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Using New Technologies in Cyber Security Solutions (3rd Edition)

A special issue of Computers (ISSN 2073-431X). This special issue belongs to the section "ICT Infrastructures for Cybersecurity".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 2016

Special Issue Editors

Prof. Dr. Leandros Maglaras

E-Mail Website
Guest Editor
School of Computing, Edinburgh Napier University, Edinburgh EH10 5DT, UK
Interests: critical infrastructure security; IoT security & privacy; intrusion detection systems; incident response
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Helge Janicke

E-Mail Website
Guest Editor
Centre for Securing Digital Futures, Edith Cowan University, Perth, WA 6027, Australia
Interests: cyber security; security of industrial control systems/SCADA; digital forensics; cyber physical systems
Special Issues, Collections and Topics in MDPI journals
Dr. Alexios Lekidis

E-Mail Website
Guest Editor
Department of Energy Systems, University of Thessaly, Geopolis, 41500 Larissa, Greece
Interests: industrial Internet of Things; network-based intrusion detection; incident response; 5G and next-generation networks; intelligent energy systems; vehicle-to-everything
Special Issues, Collections and Topics in MDPI journals
Dr. Mohamed Amine Ferrag

E-Mail Website
Guest Editor
College of Information Technology, United Arab Emirates University (UAEU), Al Ain 15551, United Arab Emirates
Interests: agricultural internet of things; wireless network security; network coding security; applied cryptography

Special Issue Information

Dear Colleagues,

In this Special Issue of Computers, we welcome original research articles and comprehensive reviews addressing various aspects of cyber security. Contributions presenting novel technologies, methods, and applications in the field of cyber security are encouraged. Example research areas include, but are not limited to, the following:

  • Using blockchain technologies on cyber security solutions;
  • Using LLMs, deep learning and active learning on cyber security solutions;
  • IoT, virtualization, and cloud computing security;
  • Security and privacy issues in metaverse;
  • Using pot-quantum cryptographic solutions;
  • Secure smart contracts;
  • Cyber-attacks on blockchain technology;
  • Novel cybercrimes on social media using deepfake technology.

Recently, most daily activities have shifted into the digital realm. While this digital transformation offers numerous benefits, it has also made individuals and organizations increasingly vulnerable to cyber-attacks. According to recent reports, by 2025, cybercrime is projected to cost the global economy approximately USD 10 trillion, making it one of the most profitable illicit sectors worldwide. The volume of cyber-related crimes continues to rise, and no single technique or method has yet proven capable of effectively stopping attackers. As soon as cyber defenders develop solutions to known attacks, cybercriminals respond with new, previously unseen attack strategies—remaining, in most cases, one step ahead.

Emerging technologies such as blockchain, smart contracts, virtualization, large language models (LLMs), deep learning, active learning, and post-quantum crypto offer promising directions for advancing cyber security. Therefore, this Special Issue welcomes original research articles and reviews that apply novel technologies and methodologies to various domains within cyber security. The goal of this Issue is to present innovative ideas, expand scholarly understanding, and provide propose efficient, forward-looking solutions to counteract cybercrime.

Prof. Dr. Leandros Maglaras
Prof. Dr. Helge Janicke
Dr. Alexios Lekidis
Dr. Mohamed Amine Ferrag
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 250 words) can be sent to the Editorial Office for assessment.

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. Computers is an international peer-reviewed open access monthly 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 1800 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

  • LLM cybersecurity solutions
  • post-quantum crypto
  • deepfake attacks
  • metaverse cybersecurity

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Related Special Issues

Published Papers (3 papers)

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Research

20 pages, 5491 KB  
Article
Out-of-Time-Order Correlators as Indicators of Entropy in the Quantum Kicked Rotor
by Taukhid W. Broto, Supriadi Rustad, Ahmad Zainul Fanani, Sri Winarno and De Rosal Ignatius Moses Setiadi
Computers 2026, 15(1), 23; https://doi.org/10.3390/computers15010023 - 5 Jan 2026
Viewed by 255
Abstract
We show that Out-of-Time-Ordered Correlator (OTOC) growth in the Quantum Kicked Rotor (QKR) quantifies information scrambling rather than entropy production. Numerical simulations reproduce the quadratic OTOC scaling at resonance (ℏeff=4π) and its suppression under detuning. Bitstreams derived [...] Read more.
We show that Out-of-Time-Ordered Correlator (OTOC) growth in the Quantum Kicked Rotor (QKR) quantifies information scrambling rather than entropy production. Numerical simulations reproduce the quadratic OTOC scaling at resonance (ℏeff=4π) and its suppression under detuning. Bitstreams derived from the evolving wavefunction reveal a nonmonotonic relationship between chaos and entropy: the resonant (maximally chaotic) regime exhibits lower measured entropy due to coherent phase correlations, whereas slight detuning enhances statistical uniformity. While Out-of-Time-Ordered Correlators quantify information scrambling rather than entropy production, we show that the strength of scrambling strongly constrains the amount of classical entropy that can be extracted after measurement. Full article
(This article belongs to the Special Issue Using New Technologies in Cyber Security Solutions (3rd Edition))
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24 pages, 606 KB  
Article
A Secure Blockchain-Based MFA Dynamic Mechanism
by Vassilis Papaspirou, Ioanna Kantzavelou, Yagmur Yigit, Leandros Maglaras and Sokratis Katsikas
Computers 2025, 14(12), 550; https://doi.org/10.3390/computers14120550 - 12 Dec 2025
Viewed by 636
Abstract
Authentication mechanisms attract considerable research interest due to the protective role they offer, and when they fail, the system becomes vulnerable and immediately exposed to attacks. Blockchain technology was recently incorporated to enhance authentication mechanisms through its inherited specifications that cover higher security [...] Read more.
Authentication mechanisms attract considerable research interest due to the protective role they offer, and when they fail, the system becomes vulnerable and immediately exposed to attacks. Blockchain technology was recently incorporated to enhance authentication mechanisms through its inherited specifications that cover higher security requirements. This article proposes a dynamic multi-factor authentication (MFA) mechanism based on blockchain technology. The approach combines a honeytoken authentication method implemented with smart contracts and deploys the dynamic change of honeytokens for enhanced security. Two additional random numbers are inserted into the honeytoken within the smart contract for protection from potential attackers, forming a triad of values. The produced set is then imported into a dynamic hash algorithm that changes daily, introducing an additional layer of complexity and unpredictability. The honeytokens are securely transferred to the user through a dedicated and safe communication channel, ensuring the integrity and confidentiality of this critical authentication factor. Extensive evaluation and threat analysis of the proposed blockchain-based MFA dynamic mechanism (BMFA) demonstrate that it meets high-security standards and possesses essential properties that give prospects for future use in many domains. Full article
(This article belongs to the Special Issue Using New Technologies in Cyber Security Solutions (3rd Edition))
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22 pages, 765 KB  
Article
Evaluating Deployment of Deep Learning Model for Early Cyberthreat Detection in On-Premise Scenario Using Machine Learning Operations Framework
by Andrej Ralbovský, Ivan Kotuliak and Dennis Sobolev
Computers 2025, 14(12), 506; https://doi.org/10.3390/computers14120506 - 23 Nov 2025
Cited by 1 | Viewed by 830
Abstract
Modern on-premises threat detection increasingly relies on deep learning over network and system logs, yet organizations must balance infrastructure and resource constraints with maintainability and performance. We investigate how adopting MLOps influences deployment and runtime behavior of a recurrent-neural-network–based detector for malicious event [...] Read more.
Modern on-premises threat detection increasingly relies on deep learning over network and system logs, yet organizations must balance infrastructure and resource constraints with maintainability and performance. We investigate how adopting MLOps influences deployment and runtime behavior of a recurrent-neural-network–based detector for malicious event sequences. Our investigation includes surveying modern open-source platforms to select a suitable candidate, its implementation over a two-node setup with a CPU-centric control server and a GPU worker and performance evaluation for a containerized MLOps-integrated setup vs. bare metal. For evaluation, we use four scenarios that cross the deployment model (bare metal vs. containerized) with two different versions of software stack, using a sizable training corpus and a held-out inference subset representative of operational traffic. For training and inference, we measured execution time, CPU and RAM utilization, and peak GPU memory to find notable patterns or correlations providing insights for organizations adopting the on-premises-first approach. Our findings prove that MLOps can be adopted even in resource-constrained environments without inherent performance penalties; thus, platform choice should be guided by operational concerns (reproducibility, scheduling, tracking), while performance tuning should prioritize pinning and validating the software stack, which has surprisingly large impact on resource utilization and execution process. Our study offers a reproducible blueprint for on-premises cyber-analytics and clarifies where optimization yields the greatest return. Full article
(This article belongs to the Special Issue Using New Technologies in Cyber Security Solutions (3rd Edition))
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