Efficient DDoS Detection Based on K-FKNN in Software Defined Networks

Abstract

Software Defined Networking (SDN) centrally manages the network data layer to improve the programmability and flexibility of networks by the controller. Because of centralized control, SDN is vulnerable to Distributed Denial of Service (DDoS) attacks. In order to protect the security of SDN, a method based on K-means++ and Fast K-Nearest Neighbors (K-FKNN) is proposed for DDoS detection in SDN, and the modular detection system is presented in the controller. The detailed experiments are conducted to evaluate the system performance. The results of the experiments show that K-FKNN improves the detection accuracy and efficiency of K-Nearest Neighbors (KNN), and has high precision and stability of DDoS detection in SDN.

Keywords

• Software defined networks
• network security
• DDoS detection
• K-nearest neighbors