Abstract: The detection of DDoS (Distributed Denial of Service) attacks is essential topic under network security. DDoS attacks cause network services to become unavailable by repeatedly flooding servers with unwanted traffic. The volume, magnitude, and complexity of these attacks increased dramatically as a result of low-cost Internet connections and easily available attack tools. Both Software Defined Networking (SDN) and Deep Learning (DL) have recently found a number of practical and fascinating applications in industry and academia. SDN enables centralized management, a global view of the overall network, and configurable control planes, allowing network devices to adapt to diverse applications. When applied to diverse categorization problems, DL-based approaches outperformed classic machine learning techniques, while SDN characteristics offer better network monitoring and security of the managed network when compared to traditional networks. By inheriting the non-linearity of neural networks, they increase feature extraction and reduction from a high-dimensional dataset in an unsupervised way. An overview of deep learning algorithms for sensing distributed denial of service attacks in software-defined networks with Deep learning is presented within this article. Furthermore, SDN environment is simulated in Mininet using RYU controller. In addition, each paper's mitigation method is examined in the survey.

P. Karthika and A. Karmel, “Analysis of Different Attacks on Software Defined Network and Approaches to Mitigate using Intelligent Techniques” International Journal of Advanced Computer Science and Applications(IJACSA), 12(9), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120938

@article{Karthika2021,
title = {Analysis of Different Attacks on Software Defined Network and Approaches to Mitigate using Intelligent Techniques},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120938},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120938},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {9},
author = {P. Karthika and A. Karmel}
}