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Exploring the Potential of Artificial Intelligence to Predict Cyber Attacks: Creation, Evaluation and Comparative Analysis of Effective Models of Ensemble Methods, Isolation Forest, and Arima Cover

Exploring the Potential of Artificial Intelligence to Predict Cyber Attacks: Creation, Evaluation and Comparative Analysis of Effective Models of Ensemble Methods, Isolation Forest, and Arima

Land Forces Academy Review
Volume 30 (2025): Issue 1 (March 2025)
By: Miroslav Stefanov,  Sharon L. Burton,  Ilhan M. Akbas and  Sean Crouse  
Open Access
|Mar 2025
Authors

Authors

Miroslav Stefanov

Miroslav.Stefanov@erau.edu

Embry-Riddle Aeronautical University, Daytona Beach, USA

Sharon L. Burton

SharonL.Burton@erau.edu

Embry-Riddle Aeronautical University, Daytona Beach, USA

Ilhan M. Akbas

Akbasm@erau.edu

Embry-Riddle Aeronautical University, Daytona Beach, USA

Sean Crouse

Crouses2@Erau.edu

Embry-Riddle Aeronautical University, Daytona Beach, USA
DOI: https://doi.org/10.2478/raft-2025-0016 | Journal eISSN: 3100-5071 | Journal ISSN: 3100-5063
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Language: English
Page range: 162 - 174
Published on: Mar 21, 2025
Published by: Nicolae Balcescu Land Forces Academy
In partnership with: Paradigm Publishing Services
Keywords:
anomaly detection,
artificial intelligence,
cyber attack prediction,
cybersecurity,
machine learning models
Related subjects:
Social sciences,
Political science,
Political science, other,
Business and economics,
Business management,
Business management, other,
Social sciences,
Education,
Education, other,
Engineering,
Electrical engineering,
Fundamentals of electrical engineering

© 2025 Miroslav Stefanov, Sharon L. Burton, Ilhan M. Akbas, Sean Crouse, published by Nicolae Balcescu Land Forces Academy
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 30 (2025): Issue 1 (March 2025)
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