DDoS Attack Detection Using Ensemble Machine Learning Models with RFE Algorithm

Abstract

There are several types of Cyber-Security Attacks today. In this paper, we focus on Distributed Denial of Service Attack (DDoS-Attack). DDoS-Attack is a vicious attempt to disrupt normal internet traffic by using DDoS traffic to the target server. Today, Artificial Intelligence is used to solve many problems. Therefore, this research introduces the ensemble machine learning models with RFE algorithm to enhance the detection efficiency of DDoSAttack floods. We compare the performance of the proposed algorithm with the other well-known algorithms in terms of time efficiency, accuracy and CPU-usage. Four types of accuracy are considered. Proposed ensemble machine learning algorithm usually saves more on computing resources than other techniques that use neural networks. From the results, we found that the proposed algorithm offers better performance than other algorithms in term of accuracy, precision, testing time and CPU-usage.