Open Access

ARTICLE

Detecting and Mitigating Distributed Denial of Service Attacks in Software-Defined Networking

Abdullah M. Alnajim^1,*, Faisal Mohammed Alotaibi^2,#, Sheroz Khan^3,#

1 Department of Information Technology, College of Computer, Qassim University, Buraydah, 51452, Saudi Arabia
2 College of Computer Engineering and Sciences, Department of information system, Prince Sattam bin Abdulaziz University, Al-Kharj, 16273, Saudi Arabia
3 Department of Electrical Engineering, College of Engineering and Information Technology, Onaizah Colleges, Qassim, 56447, Saudi Arabia

* Corresponding Author: Abdullah M. Alnajim. Email:
# These authors contributed equally to this work

(This article belongs to the Special Issue: Empowered Connected Futures of AI, IoT, and Cloud Computing in the Development of Cognitive Cities)

Computers, Materials & Continua 2025, 83(3), 4515-4535. https://doi.org/10.32604/cmc.2025.063139

Received 06 January 2025; Accepted 02 April 2025; Issue published 19 May 2025

Abstract

Distributed denial of service (DDoS) attacks are common network attacks that primarily target Internet of Things (IoT) devices. They are critical for emerging wireless services, especially for applications with limited latency. DDoS attacks pose significant risks to entrepreneurial businesses, preventing legitimate customers from accessing their websites. These attacks require intelligent analytics before processing service requests. Distributed denial of service (DDoS) attacks exploit vulnerabilities in IoT devices by launching multi-point distributed attacks. These attacks generate massive traffic that overwhelms the victim’s network, disrupting normal operations. The consequences of distributed denial of service (DDoS) attacks are typically more severe in software-defined networks (SDNs) than in traditional networks. The centralised architecture of these networks can exacerbate existing vulnerabilities, as these weaknesses may not be effectively addressed in this model. The preliminary objective for detecting and mitigating distributed denial of service (DDoS) attacks in software-defined networks (SDN) is to monitor traffic patterns and identify anomalies that indicate distributed denial of service (DDoS) attacks. It implements measures to counter the effects of DDoS attacks, and ensure network reliability and availability by leveraging the flexibility and programmability of SDN to adaptively respond to threats. The authors present a mechanism that leverages the OpenFlow and sFlow protocols to counter the threats posed by DDoS attacks. The results indicate that the proposed model effectively mitigates the negative effects of DDoS attacks in an SDN environment.

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Keywords

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