Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Fu...
Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network
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Publisher
Switzerland: MDPI AG
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Language
English
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Publisher
Switzerland: MDPI AG
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Contents
Decoupled data and control planes in Software Defined Networks (SDN) allow them to handle an increasing number of threats by limiting harmful network links at the switching stage. As storage, high-end servers, and network devices, Network Function Virtualization (NFV) is designed to replace purpose-built network elements with VNFs (Virtualized Netw...
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Full title
Predicting Attack Pattern via Machine Learning by Exploiting Stateful Firewall as Virtual Network Function in an SDN Network
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TN_cdi_doaj_primary_oai_doaj_org_article_95ea309bf911433bbcd8ca9930c4ed96
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_95ea309bf911433bbcd8ca9930c4ed96
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ISSN
1424-8220
E-ISSN
1424-8220
DOI
10.3390/s22030709
