DETECTION OF HTTP FLOOD ATTACKS BASED ON MACHINE LEARNING ALGORITHMS

Norbek Karimov, Furkat Rakhmatov, Oybek Xolmuminov

Кимёвий технология. Назорат ва бошқарув · 2025-yil

Annotatsiya

This paper analyzes the effectiveness of Random Forest and SVM models for detecting HTTP Flood attacks. Experimental results demonstrate that both models achieve high accuracy. Evaluation was conducted using Precision, Recall, and F1 Score metrics. Additionally, key features of network traffic were extracted through correlation analysis to enable real-time application of the models in attack detection. The findings provide important insights into detecting DDoS attacks using machine learning and improving model performance.

Maqola ma’lumotlari
MualliflarNorbek Karimov, Furkat Rakhmatov, Oybek Xolmuminov
JurnalКимёвий технология. Назорат ва бошқарув
Nashr sanasi2025-04-30
Jild2025
Son2
Betlar68-73
Tilen
DOI10.59048/2181-1105.1663

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