Employing Machine Learning in Building Intelligent Systems for the Protection of Electronic Resources

ТАТУ хабарлари · 2025-yil

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Modern electronic resources and web applications are exposed to numerous cyber threats, including DDoS attacks, SQL injections, XSS attacks, Slowloris, and multi-vector attacks.This article presents an intelligent system for detecting and preventing cyber threats, developed based on hybrid traffic analysis methods.The system architecture utilizes SDN/NFV technologies for dynamic scaling and integrates machine learning algorithms: PNHAD (Poisson-Normal Hybrid Anomaly Detection), XGBoost, CRNN/LSTM, and the hybrid adaptive ensemble HAEDFS.Experimental studies on the open datasets CIC-IDS2017 and UNSW-NB15 demonstrated high attack classification accuracy (up to 99.95%) with a low false positive rate (<0.5%).The proposed solution provides adaptive and intelligent protection for electronic resources and can be recommended for implementation in critical infrastructures.

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JurnalТАТУ хабарлари
Nashr sanasi2025-09-12
DOI10.61663/252tuitmct4

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