Analyzing the Impact of DDoS Attack over the Server using ANN Boosting Classifier

Abstract

Throughout the past twenty years, there has been a substantial expansion in the utilization of services and applications reliant on the Internet. Currently, approximately 57% of the world's population engages with the Internet. As a result, there has been a notable increase in the attention directed towards Internet security. Throughout its existence, the Internet has remained susceptible to various security challenges, including threats like Worms, port scans, denial of service attacks, distributed denial of service attacks, and Trojans. Service environment is against high-rate DDoS flooding attacks effectively through the use of a two-level security mechanism. Level-I and Level-II were implemented using an entropy-based mechanism and the ANN based boosting classifier (ANN-BC), respectively. First, traffic instances pass through the Level-I module. Next, the traffic instances pass through the Level-II module. Essential features extracted from the flow information to improve the accuracy rate included the precision, recall, F1-score and loss.