<div class="csl-bib-body">
<div class="csl-entry">Streibelt, F., Lindorfer, M., Gürses, S., Hernández Gañán, C., & Fiebig, T. (2023). Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets. In <i>Passive and Active Measurement : 24th International Conference, PAM 2023, Virtual Event, March 21–23, 2023, Proceedings</i> (pp. 209–226). Springer. https://doi.org/10.1007/978-3-031-28486-1_10</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/189851
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dc.description.abstract
Researchers and practitioners often face the issue of having to attribute an IP address to an organization. For current data this is comparably easy, using services like whois or other databases. Similarly, for historic data, several entities like the RIPE NCC provide websites that provide access to historic records. For large-scale network measurement work, though, researchers often have to attribute millions of addresses. For current data, Team Cymru provides a bulk whois service which allows bulk address attribution. However, at the time of writing, there is no service available that allows historic bulk attribution of IP addresses. Hence, in this paper, we introduce and evaluate our ‘Back-to-the-Future whois’ service, allowing historic bulk attribution of IP addresses on a daily granularity based on CAIDA Routeviews aggregates. We provide this service to the community for free, and also share our implementation so researchers can run instances themselves.
en
dc.language.iso
en
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dc.relation.ispartofseries
Lecture Notes in Computer Science
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
Network Measurements
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dc.subject
IP Attribution
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dc.subject
Historic Datasets
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dc.subject
Internet Architecture
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dc.subject
WHOIS Service
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dc.title
Back-to-the-Future Whois: An IP Address Attribution Service for Working with Historic Datasets
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dc.type
Inproceedings
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dc.type
Konferenzbeitrag
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
Max Planck Institute for Informatics, Germany
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dc.contributor.affiliation
Delft University of Technology, Netherlands (the)
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dc.contributor.affiliation
Delft University of Technology, Netherlands (the)
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dc.contributor.affiliation
Max Planck Institute for Informatics, Germany
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dc.relation.isbn
978-3-031-28486-1
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dc.relation.issn
0302-9743
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dc.description.startpage
209
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dc.description.endpage
226
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dc.rights.holder
The Author(s) 2023
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dc.type.category
Full-Paper Contribution
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dc.relation.eissn
1611-3349
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tuw.booktitle
Passive and Active Measurement : 24th International Conference, PAM 2023, Virtual Event, March 21–23, 2023, Proceedings