Enhancing DDoS attack detection in software-defined networks with entropy-based techniques

Gorine, Adam; Abdelrahman, Mohamed

Abstract

The introduction of Software-Defined Networks (SDN) represents significant advancements in network design by separating control and forwarding planes. While SDN improves network administration productivity, it has many vulnerabilities which hackers can exploit. One such cyber-attack is Distributed Denial of Service (DDoS), which leads to many challenges. This paper aims to assess SDN vulnerabilities by using a novel technique, Entropy, that can detect DDoS attacks at an early stage. The methodology relies on Entropy to identify abnormal network behaviour, which may indicate DDoS attacks. In addition, a novel mitigation technique using flow drop rules enables the rapid and targeted suppression of malicious traffic. Therefore, it enhances the security of SDN network devices. The solution implements a three-stage DDoS attack detection system for the SDN environment. It involves data gathering, entropy calculation, and threshold-based detection to identify potential attacks.

• Journal Article Type: Article
• Acceptance Date: Apr 4, 2024
• Publication Date: 2024
• Deposit Date: Apr 23, 2024
• Journal: International Research Journal of Advanced Engineering and Science
• Electronic ISSN: 2455-9024
• Peer Reviewed: Peer Reviewed
• Volume: 9
• Issue: 2
• Pages: 45-53
• Keywords: Software-defined networks (SDN); DDoS Attacks; Entropy-Based Detection; Flow Drop Rules; Network Security; Threat detection
• Public URL: https://uwe-repository.worktribe.com/output/11882343
• Publisher URL: https://irjaes.com/volume-9-issue-2/