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Journal of Discrete Mathematical Sciences and Cryptography cover
Open Access ·Peer-reviewed·ISSN (Online): 2169-0065·ISSN (Print): 0972-0529

Monthly Journal: Publishes theoretical and applied research in all areas of Discrete Mathematical Sciences, Cryptography, Combinatorics, Elliptic Curves and Information Security.

Issues up to 2022 co-published with and available at:Taylor & Francis Online
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Open Access Research Article

Utilizing discrete structure and applied algebra to model and analysis network resilience against cyber attack

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pp. 885–893Vol. 29Issue 2-BFebruary 2026DOI: 10.47974/JDMSC-2539 Crossmark XML
Received:
07 May 2025
Published Online:
31 Dec 2025
Article type:
Research Article
Language:
EN
Article no.:
JDMSC-2539
Pages:
885–893

Abstract

This paper offers a novel method for modeling and assessing network resilience against cyber-attacks by utilizing discrete structures and algebraic techniques. Utilizing edge and node representations taken from actual intrusion detection datasets build a network graph and examine its structural aspects to identify attack trends and resilience traits. The selection of key characteristics via correlation analysis, supervised machine learning classifiers—Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN)—are used to predict and categorize attack types. Confusion matrices and common classification metrics, accuracy, precision-, recall, and F1-score-0.99, are used to assess the models. This research supports SDG 9 by advancing secure and resilient infrastructure through innovative use of algebra and discrete structures. It also aligns with SDG 16 Peace Justice and strong institutions by contributing to the development of secure institutions.

Keywords

Subject Classifications

Primary 68M250Secondary 68M99

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