Detecting Distributed DoS Attacks on SDN using Machine Learning (ML) Methods

The DDoS attack is a well-known malicious attack that aims to interrupt traffic of the server. A DDoS attack involves the coordination of multiple systems to target a specific host simultaneously. SDN is a Software Defined Network which is a type of network layout that permits the virtual design, and creation of hardware components and also has the ability to dynamically change the network settings. Even though Software Defined Network (SDN) is an efficient approach, it remains vulnerable to DDoS attacks. This article proposes a novel system to detect whether the network is safe or attacked. The proposed system also lessens the limitations imposed by conventional and other existing techniques. Decision Tree (DT), one of the various types of ML algorithms, is used here to identify the potentially malicious traffic.