An adaptive multistage intrusion detection and prevention system in software defined networking environment.
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| Title: | An adaptive multistage intrusion detection and prevention system in software defined networking environment. |
|---|---|
| Authors: | Maheswaran, N1 (AUTHOR) nmaheswaran97@gmail.com, Bose, S1 (AUTHOR), Natarajan, Buvaneswari2 (AUTHOR) |
| Source: | Automatika: Journal for Control, Measurement, Electronics, Computing & Communications. Dec2024, Vol. 65 Issue 4, p1364-1378. 15p. |
| Subjects: | Network operating system, Systems software, Infrastructure (Economics), Internet security, Computer network security, Software-defined networking |
| Abstract: | The advancements made in Software-Defined Networking (SDN) technology seem quite promising, with potential wide application in managing and controlling the latest network infrastructures. SDN technology decouples the control plane from the data plane, enabling effective and flexible network management. However, this dynamic phenomenon brings new security challenges. With the increasing dynamism and programmable nature of networks, conventional security protocols may not sufficient to protect against advanced and sophisticated attacks. Although Intrusion Detection Systems (IDSs) have been extensively applied for identifying and preventing security threats in traditional network environments, IDS models designed specifically for traditional network requirements may not be adequate for SDN environments. These issues may stem from the static nature of conventional networks, contrasting with the dynamicity of advanced SDN networks, and the traditional IDS's inability to adapt to the dynamic nature of SDN. To address these challenges, the current research proposes a novel Deep Hybrid IDS model to enhance network security in SDN environments and prevent attacks using Scapy. The proposed model detects signature-based attacks by integrating Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) for real-time simulated datasets, achieving an accuracy of 97.8%, which is comparatively better than existing models. [ABSTRACT FROM AUTHOR] |
| Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 181233897 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: An adaptive multistage intrusion detection and prevention system in software defined networking environment. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Maheswaran%2C+N%22">Maheswaran, N</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> nmaheswaran97@gmail.com</i><br /><searchLink fieldCode="AR" term="%22Bose%2C+S%22">Bose, S</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Natarajan%2C+Buvaneswari%22">Natarajan, Buvaneswari</searchLink><relatesTo>2</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Automatika%3A+Journal+for+Control%2C+Measurement%2C+Electronics%2C+Computing+%26+Communications%22">Automatika: Journal for Control, Measurement, Electronics, Computing & Communications</searchLink>. Dec2024, Vol. 65 Issue 4, p1364-1378. 15p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Network+operating+system%22">Network operating system</searchLink><br /><searchLink fieldCode="DE" term="%22Systems+software%22">Systems software</searchLink><br /><searchLink fieldCode="DE" term="%22Infrastructure+%28Economics%29%22">Infrastructure (Economics)</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+security%22">Internet security</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+network+security%22">Computer network security</searchLink><br /><searchLink fieldCode="DE" term="%22Software-defined+networking%22">Software-defined networking</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The advancements made in Software-Defined Networking (SDN) technology seem quite promising, with potential wide application in managing and controlling the latest network infrastructures. SDN technology decouples the control plane from the data plane, enabling effective and flexible network management. However, this dynamic phenomenon brings new security challenges. With the increasing dynamism and programmable nature of networks, conventional security protocols may not sufficient to protect against advanced and sophisticated attacks. Although Intrusion Detection Systems (IDSs) have been extensively applied for identifying and preventing security threats in traditional network environments, IDS models designed specifically for traditional network requirements may not be adequate for SDN environments. These issues may stem from the static nature of conventional networks, contrasting with the dynamicity of advanced SDN networks, and the traditional IDS's inability to adapt to the dynamic nature of SDN. To address these challenges, the current research proposes a novel Deep Hybrid IDS model to enhance network security in SDN environments and prevent attacks using Scapy. The proposed model detects signature-based attacks by integrating Gated Recurrent Units (GRU) and Long Short-Term Memory (LSTM) for real-time simulated datasets, achieving an accuracy of 97.8%, which is comparatively better than existing models. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1080/00051144.2024.2372749 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 15 StartPage: 1364 Subjects: – SubjectFull: Network operating system Type: general – SubjectFull: Systems software Type: general – SubjectFull: Infrastructure (Economics) Type: general – SubjectFull: Internet security Type: general – SubjectFull: Computer network security Type: general – SubjectFull: Software-defined networking Type: general Titles: – TitleFull: An adaptive multistage intrusion detection and prevention system in software defined networking environment. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Maheswaran, N – PersonEntity: Name: NameFull: Bose, S – PersonEntity: Name: NameFull: Natarajan, Buvaneswari IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Text: Dec2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 00051144 Numbering: – Type: volume Value: 65 – Type: issue Value: 4 Titles: – TitleFull: Automatika: Journal for Control, Measurement, Electronics, Computing & Communications Type: main |
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