SOLUTION DETECTION DDoS ATTACK IN SOFTWARE DEFINED NETWORK

Abstract

Software-defined network (SDN) is a technology trend that big giants like Google, Facebook and Amazon apply and deploy into data centres to realize centralized data management and easy-to-scale network capabilities. However, this technology also has many potential risks and challenges, leading to loss of data and disrupting users' ability to provide services. One of the most significant challenges is Distributed Denial of Service (DDoS) attacks on SDN due to their intense impacts on the system's availability and reliability. Many state-of-the-art studies have been published to detect DDoS attacks, but these methods are only focused on the control layer of SDN. This paper aimed to detect a DDoS attack in the data layer of SDN by adopting hping3 and snort tools performed on a mininet simulator. The experimental results demonstrated that a DDoS attack was successfully initialized and then detected by snort in order to warn the administrator about the network connection status.