ScholarLens Back to search
2021•Unpublished venueRequires access

A Survey on Detecting Internet Routing Anomalies Using Machine Learning

Ali Hassan Muosa, Abdulalem Ali

Open publisher page 1 citations

Abstract

The Border Gateway Protocol (BGP) used to exchange IP prefixes on the internet allowing incremental path vector routing protocol and attainability between Autonomous Systems (ASes), giving proficient activity of worldwide internet. Historically speaking, BGP anomalies causes upset of ASes at a wide range, i.e., recognizing them is vital. In the current time, Machine Learning (ML) strategies  guaranty improved BGP irregularity recognition utilizing volume, and way highlights of BGP update messages, that is regularly boisterous, and bursty. In this paper, we review and arranges these anomalies and talks about the latest procedures used to recognize inconsistencies. We additionally,study various key prerequisites for the up-and-coming of detecting internet routing anomalies procedures.

About this research paper

What this paper is about

The Border Gateway Protocol (BGP) used to exchange IP prefixes on the internet allowing incremental path vector routing protocol and attainability between Autonomous Systems (ASes), giving proficient activity of worldwide internet. Historically speaking, BGP anomalies causes upset of ASes at a wide range, i.e., recognizing them is vital. In the current time, Machine Learning (ML) strategies  guaranty improved BGP irregularity recognition utilizing volume, and way highlights of BGP update messages, that is regularly boisterous, and bursty. In this paper, we review and arranges these anomalies and talks about the latest procedures used to recognize inconsistencies. We additionally,study various key prerequisites for the up-and-coming of detecting internet routing anomalies procedures.

Why it matters

OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

The Border Gateway Protocol (BGP) used to exchange IP prefixes on the internet allowing incremental path vector routing protocol and attainability between Autonomous Systems (ASes), giving proficient activity of worldwide internet. Historically speaking, BGP anomalies causes upset of ASes at a wide range, i.e., recognizing them is vital. In the current time, Machine Learning (ML) strategies  guaranty improved BGP irregularity recognition utilizing volume, and way highlights of BGP update messages, that is regularly boisterous, and bursty. In this paper, we review and arranges these anomalies and talks about the latest procedures used to recognize inconsistencies. We additionally,study various key prerequisites for the up-and-coming of detecting internet routing anomalies procedures.

Key concepts: Border Gateway Protocol, Default-free zone, Computer science, The Internet, Autonomous system (mathematics), Distance-vector routing protocol, Routing (electronic design automation), Computer network

Related papers

Related paper 1Related paper 2Related paper 3
Back to paper searchBrowse research topicsOriginal source
A Survey on Detecting Internet Routing Anomalies Using Machine Learning — Research Paper | ScholarLens