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Optimized AI-Based Intrusion Detection System for Accurate DDoS Attack Detection

This paper proposes an optimized AI-based intrusion detection system that utilizes GridSearchCV to tune six machine learning and deep learning models on the CICDDoS2019 dataset, demonstrating that Random Forest and XGBoost achieve superior accuracy and efficiency in detecting various DDoS attacks compared to other algorithms.

Original authors: Rodrigue SAOUNGOUMI SOURPELE, Patalet LAYIBE, Franklin TCHAKOUNTE, Blaise Omer YENKE, Ado Adamou ABBA ARI

Published 2026-09-02
📖 1 min read☕ Coffee break read

Original authors: Rodrigue SAOUNGOUMI SOURPELE, Patalet LAYIBE, Franklin TCHAKOUNTE, Blaise Omer YENKE, Ado Adamou ABBA ARI

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

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