A <scp>BGP</scp> Hijacking Detection System with <scp>BGP</scp> Messages at Multiple Measurement Points

Recently, network security incidents have been increasing as the Internet continues to expand. One such incident, BGP hijacking, has gained attention because it can cause major disruptions to Autonomous Systems (AS) through network attacks. Previous studies on detecting BGP hijacking have focused on analyzing BGP messages collected from a single router and identifying incidents using a Multi‐Layer Perceptron (MLP). However, this approach is limited and cannot detect incidents caused by organizations other than ISPs. To overcome this limitation, we propose a new method that uses BGP messages collected from multiple measurement points and applies advanced machine learning techniques to improve detection accuracy. © 2025 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

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Publication Details

Journal
IEEJ Transactions on Electrical and Electronic Engineering
Published
2025-05-08
DOI
https://doi.org/10.1002/tee.70058
Citations
1
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
1.49

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article

A BGP Hijacking Detection System with BGP Messages at Multiple Measurement Points

Kimihiro Mizutani, Hisayoshi Shimizu
1 citations
IEEJ Transactions on Electrical and Electronic Engineering
Network Security and Intrusion Detection
1.49
article

A BGP Hijacking Detection System with BGP Messages at Multiple Measurement Points

Kimihiro Mizutani, Hisayoshi Shimizu
article en
1 citations

Abstract

Recently, network security incidents have been increasing as the Internet continues to expand. One such incident, BGP hijacking, has gained attention because it can cause major disruptions to Autonomous Systems (AS) through network attacks. Previous studies on detecting BGP hijacking have focused on analyzing BGP messages collected from a single router and identifying incidents using a Multi‐Layer Perceptron (MLP). However, this approach is limited and cannot detect incidents caused by organizations other than ISPs. To overcome this limitation, we propose a new method that uses BGP messages collected from multiple measurement points and applies advanced machine learning techniques to improve detection accuracy. © 2025 The Author(s). IEEJ Transactions on Electrical and Electronic Engineering published by Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

IEEJ Transactions on Electrical and Electronic EngineeringVol. 20(10)
Kindai University (JP)
Japan Society for the Promotion of Science
Openalex Percentile: Top 18%
Network Security and Intrusion Detection
1.49
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A <scp>BGP</scp> Hijacking Detection System with <scp>BGP</scp> Messages at Multiple Measurement Points — Kimihiro Mizutani, Hisayoshi Shimizu · IEEJ Transactions on Electrical and Electronic Engineering (2025) | TGRS Research Map | TGRS