Machine learning in an SDN network environment for DoS attacks

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dc.careerEscuela de Ingeniería en Sistemases
dc.category.authorprincipalen_US
dc.contributor.authorChafla Altamirano, Juan Francisco
dc.contributor.correspondingChafla Altamirano, Juan Francisco
dc.countryEcuadores
dc.date.accessioned2023-11-04T21:32:17Z
dc.date.available2023-11-04T21:32:17Z
dc.date.issued2020-01
dc.dedication.authorTCes
dc.description.abstractDenial of service (DoS) attacks in Software-Defined Network (SDN) environments are increasing despite the capabilities and benefits of SDN. Software-based traffic analysis, centralized control and automatic information forwarding offered by SDN, makes it easier to detect and react effectively to DoS attacks; however, the security of the SDN itself has not yet been resolved, and there are a number of potential vulnerabilities not only of the DoS type, on the SDN platforms. In this document, we review some applications and defense mechanisms to mitigate these types of attacks in an SDN network environment. This work could help us to understand the advantages of SDNs compared to current network architectures, without leaving aside the security issue that will continue to be maintained over the years.en_US
dc.facultyIngenieríaes
dc.id.author0603003609
dc.id.type1
dc.identifier.doihttps://doi.org/10.1007/978-3-030-37221-7_20
dc.identifier.isbn9783030372200
dc.identifier.isbn9783030372217
dc.identifier.urihttps://repositorio.puce.edu.ec/handle/123456789/4998
dc.identifier.urihttps://link.springer.com/chapter/10.1007/978-3-030-37221-7_20
dc.indexed.databaseOtheres
dc.language.isoen
dc.list.authorsDominguez, M., Maya, E., Bosmediano, C., Escobar, C., Chafla, J. & Bedón, A.
dc.magazine.pageRange231–243
dc.magazine.titleAdvances in Intelligent Systems and Computingen_US
dc.magazine.volumeChapter1
dc.rightsOpenAccessen
dc.statepublisheden_US
dc.subjectSeguridad informáticaes
dc.subjectProtección de datoses
dc.subjectSistemas de seguridades
dc.subjectSeguridad informática
dc.subjectProtección de datos
dc.subjectSistemas de seguridad
dc.titleMachine learning in an SDN network environment for DoS attacksen_US
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