A Hybrid Ensemble Machine Learning Model for Cyber Threat Detection

Language: English

Published by Globeedit Jun 2026, 2026

6630189620 / 9786630189629

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This item is printed on demand - Print on Demand Titel. Neuware -The rapid growth of digital technologies and internet-based services has significantly increased cybersecurity risks, necessitating more effective and intelligent threat detection mechanisms. Traditional cybersecurity approaches, including signature-based and behavior-based detection techniques, often struggle to cope with the increasing complexity and diversity of modern cyberattacks. To address these limitations, this study proposes a hybrid machine learning framework for cyber threat detection and classification that combines the strengths of multiple learning algorithms through a weighted voting strategy. The proposed framework integrates six machine learning classifiers: K-Nearest Neighbors (KNN), Random Forest (RF), Naïve Bayes (NB), Support Vector Machine (SVM), Linear Discriminant Analysis (LDA), and Light Gradient Boosting (LGB). An empirical evaluation was conducted to assess their performance in both binary and multiclass classification tasks. For binary classification, the individual models achieved accuracies of 91.78% (KNN), 94.29% (RF), 82.18% (NB), 90.70% (SVM), 87.39% (LDA), and 94.24% (LGB). 216 pp. Englisch.

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Bibliographic details

Title
A Hybrid Ensemble Machine Learning Model for Cyber Threat Detection
Author
Emmanuel Ogala
Publisher
Globeedit Jun 2026
Publication year
2026
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6630189620
ISBN 13
9786630189629
Item weight
340 grams
Dimensions
220x150x13 mm

buchversandmimpf2000

Emtmannsberg, BAYE, Germany

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AbeBooks seller since January 23, 2017

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Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur

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