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Distributed Denial-Of-Service (DDoS) in Software-Defined Network Based on Artificial Neural Network and Binary Multi-Neighborhood Artificial Bee Colony (BMNABC) Algorithm
(Institute of Electrical and Electronics Engineers Inc., 2023) Ateeyah, E.; Seker, C.
In this paper, an intelligent intrusion detection system in a software-based network with metaheuristic algorithm is presented. In the proposed system, the controllers use the binary multi-neighborhood artificial bee colony Algorithm, to select the features. In the proposed method, the artificial neural network is used to classify the attach and non-attach data. For comparison of the results the machine learning algorithm such as support vector machine, decision tree, Ensemble, Navie Base, and K-NN methods has been used and evaluated. the best results have been obtained for artificial neural network and it was 98.99%, 98.97%, 98.94%, 98.95%, and 97.95% for accuracy of train, accuracy of test, precision test, and recall test, and F1 test, respectively. Also, the worst results have been obtained for the DT method and it was 97.54%, 97.56%, 97.42%, 97.76%, and 97.09% for accuracy of train, accuracy of test, precision test, and recall test, and F1 test respectively. © 2023 IEEE.