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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2504.10299 |
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| _version_ | 1866913792665845760 |
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| author | Zulan, Amit Miron, Omer Shapira, Tal Shavitt, Yuval |
| author_facet | Zulan, Amit Miron, Omer Shapira, Tal Shavitt, Yuval |
| contents | The Internet comprises tens of thousands of autonomous systems (ASes) whose commercial relationships are not publicly announced. The classification of the Type of Relationship (ToR) between ASes has been extensively studied over the past two decades due to its relevance in network routing management and security.
This paper presents a new approach to ToR classification, leveraging publicly available BGP data from the Internet Routing Registry (IRR). We show how the IRR can be mined and the results refined to achieve a large and accurate ToR database. Using a ground truth database with hundreds of entries we show that we indeed manage to obtain high accuracy. About two-thirds of our ToRs are new, namely, they were not obtained by previous works, which means that we enrich our ToR knowledge with links that are otherwise missed. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_10299 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | IRR-Based AS Type of Relationship Inference Zulan, Amit Miron, Omer Shapira, Tal Shavitt, Yuval Networking and Internet Architecture The Internet comprises tens of thousands of autonomous systems (ASes) whose commercial relationships are not publicly announced. The classification of the Type of Relationship (ToR) between ASes has been extensively studied over the past two decades due to its relevance in network routing management and security. This paper presents a new approach to ToR classification, leveraging publicly available BGP data from the Internet Routing Registry (IRR). We show how the IRR can be mined and the results refined to achieve a large and accurate ToR database. Using a ground truth database with hundreds of entries we show that we indeed manage to obtain high accuracy. About two-thirds of our ToRs are new, namely, they were not obtained by previous works, which means that we enrich our ToR knowledge with links that are otherwise missed. |
| title | IRR-Based AS Type of Relationship Inference |
| topic | Networking and Internet Architecture |
| url | https://arxiv.org/abs/2504.10299 |