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A distributed SDN-based intrusion detection system for IoT using optimized forests

Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a soft...

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Autor principal: Luo, Ke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468089/
https://www.ncbi.nlm.nih.gov/pubmed/37647336
http://dx.doi.org/10.1371/journal.pone.0290694
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author Luo, Ke
author_facet Luo, Ke
author_sort Luo, Ke
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description Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a software defined networking (SDN) is presented. In this method, the network structure is divided into a set of sub-networks using the SDN architecture, and intrusion detection is performed in each sub-network using a controller node. In order to detect intrusion in each sub-network, a decision tree optimized by black hole optimization (BHO) algorithm is used. Thus, the decision tree deployed in each sub-network is pruned by BHO, and the split points in its decision nodes are also determined in such a way that the accuracy of each tree in detecting sub-network attacks is maximized. The performance of the proposed method is evaluated in a simulated environment and its performance in detecting attacks using the NSLKDD and NSW-NB15 databases is examined. The results show that the proposed method can identify attacks in the NSLKDD and NSW-NB15 databases with an accuracy of 99.2% and 97.2%, respectively, which indicates an increase compared to previous methods.
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spelling pubmed-104680892023-08-31 A distributed SDN-based intrusion detection system for IoT using optimized forests Luo, Ke PLoS One Research Article Along with the expansion of Internet of Things (IoT), the importance of security and intrusion detection in this network also increases, and the need for new and architecture-specific intrusion detection systems (IDS) is felt. In this article, a distributed intrusion detection system based on a software defined networking (SDN) is presented. In this method, the network structure is divided into a set of sub-networks using the SDN architecture, and intrusion detection is performed in each sub-network using a controller node. In order to detect intrusion in each sub-network, a decision tree optimized by black hole optimization (BHO) algorithm is used. Thus, the decision tree deployed in each sub-network is pruned by BHO, and the split points in its decision nodes are also determined in such a way that the accuracy of each tree in detecting sub-network attacks is maximized. The performance of the proposed method is evaluated in a simulated environment and its performance in detecting attacks using the NSLKDD and NSW-NB15 databases is examined. The results show that the proposed method can identify attacks in the NSLKDD and NSW-NB15 databases with an accuracy of 99.2% and 97.2%, respectively, which indicates an increase compared to previous methods. Public Library of Science 2023-08-30 /pmc/articles/PMC10468089/ /pubmed/37647336 http://dx.doi.org/10.1371/journal.pone.0290694 Text en © 2023 Ke Luo https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Luo, Ke
A distributed SDN-based intrusion detection system for IoT using optimized forests
title A distributed SDN-based intrusion detection system for IoT using optimized forests
title_full A distributed SDN-based intrusion detection system for IoT using optimized forests
title_fullStr A distributed SDN-based intrusion detection system for IoT using optimized forests
title_full_unstemmed A distributed SDN-based intrusion detection system for IoT using optimized forests
title_short A distributed SDN-based intrusion detection system for IoT using optimized forests
title_sort distributed sdn-based intrusion detection system for iot using optimized forests
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10468089/
https://www.ncbi.nlm.nih.gov/pubmed/37647336
http://dx.doi.org/10.1371/journal.pone.0290694
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