Isa, M.M. and Mhamdi, L. orcid.org/0009-0000-6492-2088 (2022) An Adaptive Framework for Attack Mitigation in SDN Environment. In: 2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom). 2022 IEEE International Mediterranean Conference on Communications and Networking (MeditCom), 05-08 Sep 2022, Athens, Greece. IEEE , pp. 130-135. ISBN 9781665498258
Abstract
This paper proposes an adaptive framework for attack mitigation in Software Defined Network environments. A combined three level protection mechanism was introduced to support the functionality of secure SDN network operations. Entropy-based filtering was used to determine the legitimacy of a connection before a deep learning hybrid machine learning module made the second layer inspection. A health status verification of a specific targeted service will be deployed to confirm the current situation if an attack was in progress. A test bed has been developed to test the proposed adaptive framework and the result showed an average detection rate of 98.16%. The average false positive rate was 1.85%, which is very low considering to the size of dataset inspected. A proposed framework that covers protection for layers of SDN architecture were created and combined to ensure the secure and smooth operation of the network.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Keywords: | adaptive; entropy; autoencoder; network intrusion detection; network security; software defined networking (SDN) |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 21 Mar 2024 11:09 |
Last Modified: | 21 Mar 2024 11:09 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/meditcom55741.2022.9928595 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:210683 |