Towards an AS-to-Organization Map
Xue Cai, John Heidemann, Balachander Krishnamurthy and Walter Willinger
USC/Information Sciences Institute
Citation
Xue Cai, John Heidemann, Balachander Krishnamurthy and Walter Willinger. Towards an AS-to-Organization Map. Proceedings of the ACM Internet Measurement Conference (Melbourne, Australia, Nov. 2010), 199–205. [DOI] [PDF] [alt PDF]
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 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.Bibtex Citation
@inproceedings{Cai10c,
author = {Cai, Xue and Heidemann, John and Krishnamurthy, Balachander and Willinger, Walter},
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},
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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}}
}