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Recurrent Neural Network Model Based on a New Regularization Technique for Real-Time Intrusion Detection in SDN Environments
Author
Source
Security and Communication Networks
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-11-18
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Information Technology and Computer Science
Abstract EN
Software-defined networking (SDN) is a promising approach to networking that provides an abstraction layer for the physical network.
This technology has the potential to decrease the networking costs and complexity within huge data centers.
Although SDN offers flexibility, it has design flaws with regard to network security.
To support the ongoing use of SDN, these flaws must be fixed using an integrated approach to improve overall network security.
Therefore, in this paper, we propose a recurrent neural network (RNN) model based on a new regularization technique (RNN-SDR).
This technique supports intrusion detection within SDNs.
The purpose of regularization is to generalize the machine learning model enough for it to be performed optimally.
Experiments on the KDD Cup 1999, NSL-KDD, and UNSW-NB15 datasets achieved accuracies of 99.5%, 97.39%, and 99.9%, respectively.
The proposed RNN-SDR employs a minimum number of features when compared with other models.
In addition, the experiments also validated that the RNN-SDR model does not significantly affect network performance in comparison with other options.
Based on the analysis of the results of our experiments, we conclude that the RNN-SDR model is a promising approach for intrusion detection in SDN environments.
American Psychological Association (APA)
Albahar, Marwan Ali. 2019. Recurrent Neural Network Model Based on a New Regularization Technique for Real-Time Intrusion Detection in SDN Environments. Security and Communication Networks،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1210631
Modern Language Association (MLA)
Albahar, Marwan Ali. Recurrent Neural Network Model Based on a New Regularization Technique for Real-Time Intrusion Detection in SDN Environments. Security and Communication Networks No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1210631
American Medical Association (AMA)
Albahar, Marwan Ali. Recurrent Neural Network Model Based on a New Regularization Technique for Real-Time Intrusion Detection in SDN Environments. Security and Communication Networks. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1210631
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1210631