Towards an AS-to-Organization Map. Cai, X., Heidemann, J., Krishnamurthy, B., & Willinger, W. In Proceedings of the ACM Internet Measurement Conference, pages 199–205, Melbourne, Australia, November, 2010. ACM. ![Towards an AS-to-Organization Map [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex An understanding of Internet topology is central to answer various questions ranging from network resilience to peer selection or data center location. While much of prior work has examined AS-level connectivity, meaningful and relevant results from such an abstract view of Internet topology have been limited. For one, semantically, AS relationships capture business relationships and not physical connectivity. Additionally, many organizations often use multiple ASes, either to implement different routing policies, or as legacies from mergers and acquisitions. In this paper, we move beyond the traditional AS graph view of the Internet to define the problem of \emphAS-to-organization mapping. We describe our initial steps at automating the capture of the rich semantics inherent in the AS-level ecosystem where routing and connectivity intersect with organizations. We discuss preliminary methods that identify multi-AS organizations from WHOIS data and illustrate the challenges posed by the quality of the available data and the complexity of real-world organizational relationships.
@InProceedings{Cai10c,
author = "Xue Cai and John Heidemann and Balachander Krishnamurthy and Walter Willinger",
title = "Towards an {AS}-to-{Organization} Map",
booktitle = "Proceedings of the " # "ACM Internet Measurement Conference",
year = 2010,
sortdate = "2010-11-01",
project = "ant, amite",
jsubject = "topology_modeling",
pages = "199--205",
address = "Melbourne, Australia",
month = nov,
publisher = "ACM",
jlocation = "johnh: pafile",
keywords = "AS to organization mapping,
internet topology, network topology, AS topology",
doi = "http://dx.doi.org/10.1145/1879141.1879166",
url = "https://ant.isi.edu/%7ejohnh/PAPERS/Cai10c.html",
pdfurl = "https://ant.isi.edu/%7ejohnh/PAPERS/Cai10c.pdf",
myorganization = "USC/Information Sciences Institute",
copyrightholder = "ACM",
copyrightterms = " Permission to make digital or hard copies of portions of this work for personal or classroom use is granted without fee provided that the copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page in print or the first screen in digital media. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org." ,
supporting = "The inferred ground truth used in this paper is
available on request as dataset \url{USC/LANDER-as_to_org_mapping_inferred_truth-20100507}",
abstract = "An understanding of Internet topology is central to answer various
questions ranging from network resilience to peer selection or data
center location. While much of prior work has examined AS-level
connectivity, meaningful and relevant results from such an abstract
view of Internet topology have been limited. For one, semantically, AS
relationships capture business relationships and not physical
connectivity. Additionally, many organizations often use multiple
ASes, either to implement different routing policies, or as legacies
from mergers and acquisitions. In this paper, we move beyond the
traditional AS graph view of the Internet to define the problem
of \emph{AS-to-organization mapping}. We describe our initial steps at
automating the capture of the rich semantics inherent in the AS-level
ecosystem where routing and connectivity intersect with organizations.
We discuss preliminary methods that identify multi-AS organizations
from WHOIS data and illustrate the challenges posed by the quality of
the available data and the complexity of real-world organizational
relationships.",
}
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Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and/or a fee. Send written requests for republication to ACM Publications, Copyright & Permissions at the address above or fax +1 (212) 869-0481 or email permissions@acm.org.","supporting":"The inferred ground truth used in this paper is available on request as dataset ˘rlUSC/LANDER-as_to_org_mapping_inferred_truth-20100507","abstract":"An understanding of Internet topology is central to answer various questions ranging from network resilience to peer selection or data center location. While much of prior work has examined AS-level connectivity, meaningful and relevant results from such an abstract view of Internet topology have been limited. For one, semantically, AS relationships capture business relationships and not physical connectivity. Additionally, many organizations often use multiple ASes, either to implement different routing policies, or as legacies from mergers and acquisitions. In this paper, we move beyond the traditional AS graph view of the Internet to define the problem of \\emphAS-to-organization mapping. We describe our initial steps at automating the capture of the rich semantics inherent in the AS-level ecosystem where routing and connectivity intersect with organizations. 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Copyrights for components of this work owned \tby others than ACM must be honored. Abstracting with \tcredit is permitted. \totherwise, to republish, to post on servers, or to \tredistribute to lists, requires prior specific \tpermission and/or a fee. Send written requests for \trepublication to ACM Publications, Copyright & \tPermissions at the address above or fax +1 (212) \t869-0481 or email permissions@acm.org.\" ,\n\tsupporting = \"The inferred ground truth used in this paper is\n available on request as dataset \\url{USC/LANDER-as_to_org_mapping_inferred_truth-20100507}\",\n\tabstract = \"An understanding of Internet topology is central to answer various\nquestions ranging from network resilience to peer selection or data\ncenter location. While much of prior work has examined AS-level\nconnectivity, meaningful and relevant results from such an abstract\nview of Internet topology have been limited. For one, semantically, AS\nrelationships capture business relationships and not physical\nconnectivity. Additionally, many organizations often use multiple\nASes, either to implement different routing policies, or as legacies\nfrom mergers and acquisitions. In this paper, we move beyond the\ntraditional AS graph view of the Internet to define the problem\nof \\emph{AS-to-organization mapping}. We describe our initial steps at\nautomating the capture of the rich semantics inherent in the AS-level\necosystem where routing and connectivity intersect with organizations.\nWe discuss preliminary methods that identify multi-AS organizations\nfrom WHOIS data and illustrate the challenges posed by the quality of\nthe available data and the complexity of real-world organizational\nrelationships.\",\n}\n\n","author_short":["Cai, X.","Heidemann, J.","Krishnamurthy, B.","Willinger, W."],"bibbaseid":"cai-heidemann-krishnamurthy-willinger-towardsanastoorganizationmap-2010","role":"author","urls":{"Paper":"https://ant.isi.edu/%7ejohnh/PAPERS/Cai10c.html"},"keyword":["AS to organization mapping","internet topology","network topology","AS topology"],"metadata":{"authorlinks":{}}},"bibtype":"inproceedings","biburl":"https://bibbase.org/f/dHevizJoWEhWowz8q/johnh-2023-2.bib","dataSources":["YLyu3mj3xsBeoqiHK","fLZcDgNSoSuatv6aX","fxEParwu2ZfurScPY","7nuQvtHTqKrLmgu99"],"keywords":["as to organization mapping","internet topology","network topology","as topology"],"search_terms":["towards","organization","map","cai","heidemann","krishnamurthy","willinger"],"title":"Towards an AS-to-Organization Map","year":2010}