Hierarchical Classic Controllers (HCC) with an Enhanced SVM Method for DDoS Attack Detection in SDN

Shideh Yavary Mehr, Byrav Ramamurthy
December 2022
Cite DOI URL

Abstract

A centralized Software-defined Network (SDN) controller, due to its nature, faces many issues such as a single point of failure, computational complexity growth, different types of attacks, reliability challenges and scalability concerns. One of the most common fifth generation cyber-attacks is the Distributed Denial of Service (DDoS) attack. Having a single SDN controller can lead to a plethora of issues with respect to latency, computational complexity in the control plane, reachability, and scalability as the network scale increases. To address these issues, state-of-the-art approaches have investigated multiple SDN controllers in the network. The placement of these multiple controllers has drawn more attention in recent studies. In our previous work, we evaluated an Entropy-based technique and a machine learning-based Support Vector Machine (SVM) to detect DDoS using a single SDN controller. In this paper, we extend our previous work to further decrease the impact of the DDoS attacks on the SDN controller. Our new technique called Hierarchical Classic Controllers (HCC) uses SVM and Entropy methods to detect abnormal traffic which can lead to network failures caused by overwhelming a single controller. Determining the number of controllers and their best placement are major contributions in our new method. Our results show that the combination of the above three methods (HCC with SVM and Entropy), in the case of a network with 3 controllers provides greater accuracy and improves the DDoS attack detection rate to 86.12% compared to 79.03% and 81.33% using Entropy-based HCC and SVM-based HCC, respectively.

Type
Conference paper
Publication
2022 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Telecommunication Traffic Denial-of-Service Attack Computational Complexity Scalability Telecommunication Network Reliability Software Defined Networking Learning (Artificial Intelligence) 5G Mobile Communication Centralized Software-Defined Network Controller Common Fifth Generation Cyber-Attacks Computational Complexity Growth Computer Network Security Control Plane DDOS Attack Detection Rate DDoS Attacks Enhanced SVM Method Entropy Entropy Methods Entropy-Based HCC Entropy-Based Technique Hierarchial Classic Controllers Multiple Controllers Multiple SDN Controllers Network Failures Network Scale Increases Overwheliming a Single Controller Service Attack Single SDN Controller Support Vector Machines SVM-Based HCC Telecommunications
Byrav Ramamurthy
Byrav Ramamurthy
Professor & PI

My research areas include optical and wireless networks, peer-to-peer networks for multimedia streaming, network security and telecommunications. My research work is supported by the U.S. National Science Foundation, U.S. Department of Energy, U.S. Department of Agriculture, NASA, AT&T Corporation, Agilent Tech., Ciena, HP and OPNET Inc.