@inproceedings{72454a7524aa40bf93900311931e01e6,
title = "Cutting Through the Noise to Infer Autonomous System Topology",
abstract = "The Border Gateway Protocol (BGP) is a distributed protocol that manages interdomain routing without requiring a centralized record of which autonomous systems (ASes) connect to which others. Many methods have been devised to infer the AS topology from publicly available BGP data, but none provide a general way to handle the fact that the data are notoriously incomplete and subject to error. This paper describes a method for reliably inferring AS-level connectivity in the presence of measurement error using Bayesian statistical inference acting on BGP routing tables from multiple vantage points. We employ a novel approach for counting AS adjacency observations in the AS-PATH attribute data from public route collectors, along with a Bayesian algorithm to generate a statistical estimate of the AS-level network. Our approach also gives us a way to evaluate the accuracy of existing reconstruction methods and to identify advantageous locations for new route collectors or vantage points.",
author = "Leyba, {Kirtus G.} and Daymude, {Joshua J.} and Young, {Jean Gabriel} and Newman, {M. E.J.} and Jennifer Rexford and Stephanie Forrest",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 41st IEEE Conference on Computer Communications, INFOCOM 2022 ; Conference date: 02-05-2022 Through 05-05-2022",
year = "2022",
doi = "10.1109/INFOCOM48880.2022.9796874",
language = "English (US)",
series = "Proceedings - IEEE INFOCOM",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1609--1618",
booktitle = "INFOCOM 2022 - IEEE Conference on Computer Communications",
}