Using ML to Block BGP Hijacking

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dc.contributor.authorCamp, L Jean
dc.date.accessioned2025-02-20T15:56:25Z
dc.date.available2025-02-20T15:56:25Z
dc.date.issued2019
dc.descriptionThis record is for a(n) offprint of an article published in ;login: the USENIX magazine in 2019.
dc.description.abstractBorder Gateway Protocol (BGP) has proven to be resilient in the face of failures, attacks, and general maliciousness and incompetence. While there are no deployed mechanisms for automatically remediating BGP announcements that may be malicious, there have been many attempts at fixing this sorry state of affairs. In this article, I will describe some troublesome BGP events and how our tool, Bongo, uses machine learning (ML) and Layer 8 in the IP stack to detect malicious announcements and block traffic that would be diverted.
dc.description.versionoffprint
dc.identifier.citationCamp, L Jean. "Using ML to Block BGP Hijacking." ;login: the USENIX magazine, vol. 44, no. 4, pp. 6-10, 2019.
dc.identifier.otherBRITE 4734
dc.identifier.urihttps://hdl.handle.net/2022/32232
dc.language.isoen
dc.relation.journal;login: the USENIX magazine
dc.rightsThis work may be protected by copyright unless otherwise stated.
dc.titleUsing ML to Block BGP Hijacking

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