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РецензированоEN2025

MITIGATION OF DDOS ATTACKS ON WEB APPLICATIONS USING ADAPTIVE RATE-LIMITING AND ALGORITHMIC FILTERING TECHNIQUES

To‘rabekova Shirin Xaitvoy qizi

Образование наука и инновационные идеи в мире · 72-79 · 2025

Аннотация

This paper presents a hybrid approach for mitigating Distributed Denial of Service (DDoS) attacks on web applications through the integration of adaptive rate-limiting and algorithmic filtering techniques. The adaptive rate-limiting module dynamically adjusts request thresholds based on real-time traffic behavior, while the algorithmic filtering component utilizes heuristic rules and machine learning classifiers to detect and block malicious traffic. Experimental results show that this combined method significantly improves attack detection rates, reduces false positives, and maintains optimal server performance under stress. The proposed framework provides a scalable, intelligent, and effective defense strategy against modern application-layer DDoS attacks.

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«This paper presents a hybrid approach for mitigating Distributed Denial of Service (DDoS) attacks on web applications through the integration of adaptive rate-limiting and algorithmic filtering te…»

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This paper presents a hybrid approach for mitigating Distributed Denial of Service (DDoS) attacks on web applications through the integration of adaptive rate-limiting and algorithmic filtering te… Полный текст публикации CiteX не хранит — доступ к первоисточнику открывается по DOI согласно лицензии издателя и выбранному плану.

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DDoS attacks, web application security, adaptive rate-limiting, algorithmic filtering, machine learning, traffic analysis, heuristic detection, real time mitigation, cybersecurity, application-layer defense.
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