MITIGATION OF DDOS ATTACKS ON WEB APPLICATIONS USING ADAPTIVE RATE-LIMITING AND ALGORITHMIC FILTERING TECHNIQUES
##semicolon##
DDoS attacks, web application security, adaptive rate-limiting, algorithmic filtering, machine learning, traffic analysis, heuristic detection, real time mitigation, cybersecurity, application-layer defense.##article.abstract##
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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