Leveraging Mathematical Models for Proactive Cybersecurity in Multi-Layered Networked Systems- A Study

Kavitha, Rose, Joseph, Asha, and Kumar, K. Vinoth (2025) Leveraging Mathematical Models for Proactive Cybersecurity in Multi-Layered Networked Systems- A Study. In: Proceedings of the International Conference on Data Intelligence and Cognitive Informatics. pp. 492-496. From: ICDICI 2025: 6th International Conference on Data Intelligence and Cognitive Informatics, 9-11 July 2025, Tirunelveli, India.

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Abstract

In the era of increasingly complex and interconnected digital ecosystems, proactive cybersecurity has emerged as a critical requirement. This paper presents a comprehensive approach that employs advanced mathematical modeling techniques to detect, predict, and mitigate cyber threats in multi-layered networked systems. We explore and integrate methodologies from game theory, graph theory, Markov processes, control theory, and probabilistic learning to fortify defenses at the physical, network, application, and user levels. A proactive cybersecurity workflow is developed and simulated using synthetic attack data. Our results demonstrate that mathematically-informed models significantly improve risk mitigation, reduce response time, and lower the probability of successful attacks.

Item ID: 89423
Item Type: Conference Item (Research - E1)
ISBN: 9798331503130
Keywords: Markov process, Mathematical Modeling, Multi-layered network architecture, Proactive cyber security, Quantum Computing
Copyright Information: © 2025 IEEE
Date Deposited: 29 Jan 2026 02:14
FoR Codes: 46 INFORMATION AND COMPUTING SCIENCES > 4613 Theory of computation > 461307 Quantum computation @ 50%
46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460401 Cryptography @ 50%
SEO Codes: 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 100%
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