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Fingerprinting encrypted network traffic types using machine learning

dc.contributor.authorLeroux, Sam
dc.contributor.authorBohez, Steven
dc.contributor.authorMaenhaut, Pieter Jan
dc.contributor.authorMeheus, N.
dc.contributor.authorSimoens, Pieter
dc.contributor.authorDhoedt, Bart
dc.date.accessioned2021-10-25T21:49:02Z
dc.date.available2021-10-25T21:49:02Z
dc.date.issued2018-04
dc.identifier.urihttps://imec-publications.be/handle/20.500.12860/31154
dc.sourceIIOimport
dc.titleFingerprinting encrypted network traffic types using machine learning
dc.typeProceedings paper
dc.contributor.imecauthorLeroux, Sam
dc.contributor.imecauthorMaenhaut, Pieter Jan
dc.contributor.imecauthorSimoens, Pieter
dc.contributor.imecauthorDhoedt, Bart
dc.contributor.orcidimecLeroux, Sam::0000-0003-3792-5026
dc.contributor.orcidimecSimoens, Pieter::0000-0002-9569-9373
dc.contributor.orcidimecDhoedt, Bart::0000-0002-7271-7479
dc.date.embargo9999-12-31
dc.source.peerreviewyes
dc.source.beginpage1
dc.source.endpage5
dc.source.conferenceIEEE/IFIP Network Operations and Management Symposium - NOMS
dc.source.conferencedate23/04/2018
dc.source.conferencelocationTaipei Taiwan
dc.identifier.urllearning http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=8406218
imec.availabilityPublished - open access
imec.internalnotesISBN 978-1-5386-3416-5


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