talshapira/BGP2Vec
We introduce a novel approach for Autonomous System (AS) embedding using deep learning based on only BGP announcements. Using these vectors we are able to solve multiple important classification problems such as AS business types, AS Types of Relationship (ToR) and even IP hijack detection.
This project helps network analysts and security engineers understand the fundamental characteristics and relationships of Autonomous Systems (ASNs) on the Internet. By processing BGP routing announcements, it generates a numerical representation (vectors) for each ASN. This allows you to classify ASNs by their business type, determine their relationship with other ASNs (like peer or customer), and even detect potential IP hijack events.
No commits in the last 6 months.
Use this if you need to gain deeper insights into the roles and connections of ASNs from BGP data to support network analysis, security monitoring, or Internet infrastructure research.
Not ideal if you are looking for a simple, off-the-shelf tool for real-time BGP monitoring without needing to process raw BGP announcement data and train machine learning models.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Oct 25, 2023
Commits (30d)
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