Publication:

Towards Real-Time Deep Learning-Based Network Intrusion Detection on FPGA

Date

2021
Proceedings Paper
https://doi.org/10.1007/978-3-030-81645-2_9
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dc.contributor.authorLe Jeune, Laurens
dc.contributor.authorGoedeme, Toon
dc.contributor.authorMentens, Nele
dc.contributor.imecauthorMentens, Nele
dc.contributor.orcidextLe Jeune, Laurens::0000-0003-0744-4897
dc.contributor.orcidextGoedeme, Toon::0000-0002-7477-8961
dc.date.accessioned2021-12-07T07:50:02Z
dc.date.available2021-11-02T15:57:25Z
dc.date.available2021-12-07T07:50:02Z
dc.date.embargo9999-12-31
dc.date.issued2021
dc.identifier.doi10.1007/978-3-030-81645-2_9
dc.identifier.eisbn978-3-030-81645-2
dc.identifier.isbn978-3-030-81644-5
dc.identifier.issn0302-9743
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/37606
dc.publisherSPRINGER INTERNATIONAL PUBLISHING AG
dc.source.beginpage133
dc.source.conference19th International Conference on Applied Cryptography and Network Security (ACNS)
dc.source.conferencedateJUN 21-24, 2021
dc.source.conferencelocationKamakura, Japan
dc.source.endpage150
dc.source.journalna
dc.source.numberofpages18
dc.source.volume12809
dc.subject.keywordsNEURAL-NETWORKS
dc.title

Towards Real-Time Deep Learning-Based Network Intrusion Detection on FPGA

dc.typeProceedings paper
dspace.entity.typePublication
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