Towards Efficient DDoS Attack Detection for SDN: A Survey of Hybrid Deep Learning Frameworks | [International Journal of Communication Networks and Information Security • 2024]

Author(s):

1. Nawar Jumaah: Department, University of Qom, and Assistant Teacher,General Directorate of Education Second Rusafa, Iraqi Ministry of Education, Baghdad, Iraq

2. Asghar Tajoddin: Department of Electrical and Engineering, Faculty of Computer, University of Zanjan,,Iran

3. Ahmed Aljhayyish: Department, University of Imam Kadhum, Diwaniyah Sections, Iraq.

Abstract:

Software-defined networking (SDN) is a revolutionary innovation in the technology of networks with a lot of demanded attributes such as manageability and flexibility. SDN shows new risks of privacy as well as safety such as distributed denial-of-service (DDoS) attacks. DDoS attacks refer to a basic SDN network threat that leads to strict network performance disruptions. Therefore, multiple deep learning (DL) models usage like recurrent neural networks (RNN) and convolutional neural networks (CNN), efficiently raises the capability for recognizing complicated attacks. In addition, Explainable AI (XAI) methods cooperate with DL models, and transparency and interpretability also strengthen trust in security systems. Here, DDoS attack' detection concerns and responses in SDN networks applying multiple architectures given the DL were examined. In addition, it provides novel fault-tolerant SDN frameworks that could cope with DDoS attacks and guarantee the fixing of the network in crucial conditions. At last, the present paper outcomes illustrate that multiple architectures could be strong means to diagnose and counter DDoS attacks in SDN networks also show study and improvement demand in the present domain for developing new network security systems performance.

Page(s): 399-410

DOI: DOI not available

Published: Journal: International Journal of Communication Networks and Information Security, Volume: 16, Issue: 5, Year: 2024

Keywords:

DDOS Attack Detection , Explainable AI , SDN SoftwareDefined Networking , Hybrid Deep Learning Framework

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