Volume 10 , Issue 1 , PP: 08-17, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Mohammed. I. Alghamdi 1 * , Abeer. Y. Salawi 2 , Salwa. H. Alghamdi 3
Doi: https://doi.org/10.54216/JCIM.0100101
Software defined networks (SDN) remain a hot research field as it provides controllable networking operations. The SDN controller can be treated as the operating system of the SDN model and it holds the responsibility of performing different networking applications. Despite the benefits of SDN, security remains a challenging problem. At the same time, distributed denial of services (DDoS) is a typical attack on SDN owing to centralized architecture, especially at the control layer of the SDN. This article develops a new Cat Swarm Optimization with Fuzzy Rule Base Classification (CSO-FRBCC) model for cybersecurity in SDN. The presented CSO-FRBCC model intends to effectually categorize the occurrence of DDoS attacks in SDN. To achieve this, the CSO-FRBCC model primarily pre-processes the input data to transform it to a uniform format. Besides, the CSO-FRBCC model employs FRBCC classifier for the recognition and classification of intrusions. Moreover, the parameter optimization of the FRBCC classification model is adjusted by the use of cat swarm optimization (CSO) algorithm which results in improved performance. A comprehensive set of simulations were carried out on benchmark dataset and the results highlighted the enhanced outcomes of the CSO-FRBCC model over the other recent approaches.
Cybersecurity , Software Defined Networks , Fuzzy logic , Metaheuristics , Parameter optimization , Security
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