ARL-D2F: An Adaptive Rate Limiting Framework for Effective DDoS Detection and Defense using Brown’s Smoothing
Rachana Patil, Madhuri Gurale, Komal Nikhil Borate, Yogesh H. Patil, Jotiram Krishna Deshmukh · Journal of Engineering Science and Technology Review · 2025
Advancements in technology and the rapid growth of the internet have transformed it into a crucial national resource, supporting various sectors, including national security.However, these developments have also paved the way for significant network threats, with Distributed Denial-of-Service (DDoS) attacks being among the most disruptive.This study introduces an innovative Adaptive Rate Limiting with Dynamic Defense Framework (ARL-D²F) designed to detect and mitigate DDoS attacks effectively.By employing a two-phase defense mechanism consisting of immediate rate limiting and a subsequent controlled recovery phase, the framework ensures robust protection It calculates an Attack Severity Score and leverages entropy-based analysis to enhance detection accuracy.Experimental results indicate that ARL-D²F successfully reduces malicious traffic while preserving service availability, outperforming conventional methods in maintaining consistent throughput under varying attack intensities.Its adaptive and resilient design makes it a reliable solution for defending against evolving DDoS threats