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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.09910 |
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| _version_ | 1866908877176438784 |
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| author | Tan, Godfrey Poletto, Massimiliano Guttag, John Kaashoek, Frans |
| author_facet | Tan, Godfrey Poletto, Massimiliano Guttag, John Kaashoek, Frans |
| contents | Role classification involves grouping hosts into related roles. It exposes the logical structure of a network, simplifies network management tasks such as policy checking and network segmentation, and can be used to improve the accuracy of network monitoring and analysis algorithms such as intrusion detection. This paper defines the role classification problem and introduces two practical algorithms that group hosts based on observed connection patterns while dealing with changes in these patterns over time. The algorithms have been implemented in a commercial network monitoring and analysis product for enterprise networks. Results from grouping two enterprise networks show that the number of groups identified by our algorithms can be two orders of magnitude smaller than the number of hosts and that the way our algorithms group hosts highly reflects the logical structure of the networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_09910 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Role Classification of Hosts within Enterprise Networks Based on Connection Patterns Tan, Godfrey Poletto, Massimiliano Guttag, John Kaashoek, Frans Networking and Internet Architecture Cryptography and Security Role classification involves grouping hosts into related roles. It exposes the logical structure of a network, simplifies network management tasks such as policy checking and network segmentation, and can be used to improve the accuracy of network monitoring and analysis algorithms such as intrusion detection. This paper defines the role classification problem and introduces two practical algorithms that group hosts based on observed connection patterns while dealing with changes in these patterns over time. The algorithms have been implemented in a commercial network monitoring and analysis product for enterprise networks. Results from grouping two enterprise networks show that the number of groups identified by our algorithms can be two orders of magnitude smaller than the number of hosts and that the way our algorithms group hosts highly reflects the logical structure of the networks. |
| title | Role Classification of Hosts within Enterprise Networks Based on Connection Patterns |
| topic | Networking and Internet Architecture Cryptography and Security |
| url | https://arxiv.org/abs/2603.09910 |