Analytical Frameworks and Methods for Cybersecurity, 2nd Edition

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E1: Mathematics and Computer Science".

Deadline for manuscript submissions: 10 July 2025 | Viewed by 785

Special Issue Editor


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Institute of Information and Communication Technologies, Bulgarian Academy of Sciences, 1113 Sofia, Bulgaria
Interests: OR; complexity; big data; cybersecurity; cyber defence; crisis management
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Special Issue Information

Dear Colleagues,

We are inviting submissions to the Mathematics Special Issue on “Analytical Frameworks and Methods for Cybersecurity, 2nd Edition”.

Critical infrastructures, the provision of essential services as well as individual and group perceptions are increasingly under sophisticated attack through cyberspace. The application of adequate frameworks and advanced analytical methods can increase the effectiveness of mitigation and protection measures as well as the response to cyberattacks. This Special Issue is dedicated to rigorous analytics including, but not limited to, deep learning over big data to model attacks, providing situational awareness, detecting anomalies, classifying intrusion attempts, coordinating the response, optimizing resilience measures, protecting information and communications, detecting and designing countermeasures for malign online influence and disinformation, and minimizing the vulnerabilities of network and information systems and supply chains.

Prof. Dr. Todor Tagarev
Guest Editor

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Keywords

  • Cybersecurity
  • Cyber–physical systems
  • Cyber persona
  • Influence operations
  • Attack modelling
  • Situational awareness
  • Intrusion detection
  • Classification
  • Forensics
  • Risk management
  • Resilience
  • Coding
  • Cryptography
  • Artificial intelligence
  • Deep learning
 
 

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Published Papers (1 paper)

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Research

27 pages, 5252 KiB  
Article
Mathematical Modeling and Clustering Framework for Cyber Threat Analysis Across Industries
by Fahim Sufi and Musleh Alsulami
Mathematics 2025, 13(4), 655; https://doi.org/10.3390/math13040655 - 17 Feb 2025
Cited by 1 | Viewed by 562
Abstract
The escalating prevalence of cyber threats across industries underscores the urgent need for robust analytical frameworks to understand their clustering, prevalence, and distribution. This study addresses the challenge of quantifying and analyzing relationships between 95 distinct cyberattack types and 29 industry sectors, leveraging [...] Read more.
The escalating prevalence of cyber threats across industries underscores the urgent need for robust analytical frameworks to understand their clustering, prevalence, and distribution. This study addresses the challenge of quantifying and analyzing relationships between 95 distinct cyberattack types and 29 industry sectors, leveraging a dataset of 9261 entries filtered from over 1 million news articles. Existing approaches often fail to capture nuanced patterns across such complex datasets, justifying the need for innovative methodologies. We present a rigorous mathematical framework integrating chi-square tests, Bayesian inference, Gaussian Mixture Models (GMMs), and Spectral Clustering. This framework identifies key patterns, such as 1150 Zero-Day Exploits clustered in the IT and Telecommunications sector, 732 Advanced Persistent Threats (APTs) in Government and Public Administration, and Malware with a posterior probability of 0.287 dominating the Healthcare sector. Temporal analyses reveal periodic spikes, such as in Zero-Day Exploits, and a persistent presence of Social Engineering Attacks, with 1397 occurrences across industries. These findings are quantified using significance scores (mean: 3.25 ± 0.7) and posterior probabilities, providing evidence for industry-specific vulnerabilities. This research offers actionable insights for policymakers, cybersecurity professionals, and organizational decision makers by equipping them with a data-driven understanding of sector-specific risks. The mathematical formulations are replicable and scalable, enabling organizations to allocate resources effectively and develop proactive defenses against emerging threats. By bridging mathematical theory to real-world cybersecurity challenges, this study delivers impactful contributions toward safeguarding critical infrastructure and digital assets. Full article
(This article belongs to the Special Issue Analytical Frameworks and Methods for Cybersecurity, 2nd Edition)
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