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Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network

Wireless Local Area Networks (WLANs) have become an increasingly popular mode of communication and networking, with a wide range of applications in various fields. However, the increasing popularity of WLANs has also led to an increase in security threats, including denial of service (DoS) attacks....

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Main Authors: Abdallah Elhigazi Abdallah, Mosab Hamdan, Mohammed S. M. Gismalla, Ashraf Osman Ibrahim Elsayed, Nouf Saleh Aljurayban
Format: Article
Language:English
English
Published: MDPI 2023
Subjects:
QA75.5-76.95 Electronic computers. Computer science
T10.5-11.9 Communication of technical information
Online Access:https://eprints.ums.edu.my/id/eprint/42236/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/42236/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/42236/
https://doi.org/10.3390/s23052663
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spelling my.ums.eprints.422362024-12-16T03:23:25Z https://eprints.ums.edu.my/id/eprint/42236/ Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network Abdallah Elhigazi Abdallah Mosab Hamdan Mohammed S. M. Gismalla Ashraf Osman Ibrahim Elsayed Nouf Saleh Aljurayban QA75.5-76.95 Electronic computers. Computer science T10.5-11.9 Communication of technical information Wireless Local Area Networks (WLANs) have become an increasingly popular mode of communication and networking, with a wide range of applications in various fields. However, the increasing popularity of WLANs has also led to an increase in security threats, including denial of service (DoS) attacks. In this study, management-frames-based DoS attacks, in which the attacker floods the network with management frames, are particularly concerning as they can cause widespread disruptions in the network. Attacks known as denial of service (DoS) can target wireless LANs. None of the wireless security mechanisms in use today contemplate defence against them. At the MAC layer, there are multiple vulnerabilities that can be exploited to launch DoS attacks. This paper focuses on designing and developing an artificial neural network (NN) scheme for detecting management-frames-based DoS attacks. The proposed scheme aims to effectively detect fake de-authentication/disassociation frames and improve network performance by avoiding communication interruption caused by such attacks. The proposed NN scheme leverages machine learning techniques to analyse patterns and features in the management frames exchanged between wireless devices. By training the NN, the system can learn to accurately detect potential DoS attacks. This approach offers a more sophisticated and effective solution to the problem of DoS attacks in wireless LANs and has the potential to significantly enhance the security and reliability of these networks. According to the experimental results, the proposed technique exhibits higher effectiveness in detection compared to existing methods, as evidenced by a significantly increased true positive rate and a decreased false positive rate. MDPI 2023 Article NonPeerReviewed text en https://eprints.ums.edu.my/id/eprint/42236/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/42236/2/FULL%20TEXT.pdf Abdallah Elhigazi Abdallah and Mosab Hamdan and Mohammed S. M. Gismalla and Ashraf Osman Ibrahim Elsayed and Nouf Saleh Aljurayban (2023) Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network. Sensors, 23. pp. 1-13. https://doi.org/10.3390/s23052663
institution Universiti Malaysia Sabah
building UMS Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Sabah
content_source UMS Institutional Repository
url_provider http://eprints.ums.edu.my/
language English
English
topic QA75.5-76.95 Electronic computers. Computer science
T10.5-11.9 Communication of technical information
spellingShingle QA75.5-76.95 Electronic computers. Computer science
T10.5-11.9 Communication of technical information
Abdallah Elhigazi Abdallah
Mosab Hamdan
Mohammed S. M. Gismalla
Ashraf Osman Ibrahim Elsayed
Nouf Saleh Aljurayban
Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
description Wireless Local Area Networks (WLANs) have become an increasingly popular mode of communication and networking, with a wide range of applications in various fields. However, the increasing popularity of WLANs has also led to an increase in security threats, including denial of service (DoS) attacks. In this study, management-frames-based DoS attacks, in which the attacker floods the network with management frames, are particularly concerning as they can cause widespread disruptions in the network. Attacks known as denial of service (DoS) can target wireless LANs. None of the wireless security mechanisms in use today contemplate defence against them. At the MAC layer, there are multiple vulnerabilities that can be exploited to launch DoS attacks. This paper focuses on designing and developing an artificial neural network (NN) scheme for detecting management-frames-based DoS attacks. The proposed scheme aims to effectively detect fake de-authentication/disassociation frames and improve network performance by avoiding communication interruption caused by such attacks. The proposed NN scheme leverages machine learning techniques to analyse patterns and features in the management frames exchanged between wireless devices. By training the NN, the system can learn to accurately detect potential DoS attacks. This approach offers a more sophisticated and effective solution to the problem of DoS attacks in wireless LANs and has the potential to significantly enhance the security and reliability of these networks. According to the experimental results, the proposed technique exhibits higher effectiveness in detection compared to existing methods, as evidenced by a significantly increased true positive rate and a decreased false positive rate.
format Article
author Abdallah Elhigazi Abdallah
Mosab Hamdan
Mohammed S. M. Gismalla
Ashraf Osman Ibrahim Elsayed
Nouf Saleh Aljurayban
author_facet Abdallah Elhigazi Abdallah
Mosab Hamdan
Mohammed S. M. Gismalla
Ashraf Osman Ibrahim Elsayed
Nouf Saleh Aljurayban
author_sort Abdallah Elhigazi Abdallah
title Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
title_short Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
title_full Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
title_fullStr Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
title_full_unstemmed Detection of management-Frames-Based Denial-of-Service Attack in Wireless LAN network using artificial neural network
title_sort detection of management-frames-based denial-of-service attack in wireless lan network using artificial neural network
publisher MDPI
publishDate 2023
url https://eprints.ums.edu.my/id/eprint/42236/1/ABSTRACT.pdf
https://eprints.ums.edu.my/id/eprint/42236/2/FULL%20TEXT.pdf
https://eprints.ums.edu.my/id/eprint/42236/
https://doi.org/10.3390/s23052663
_version_ 1818835194377928704
score 13.226497

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