Improving AS relationship inference using PoPs

Lior Neudorfer, Yuval Shavitt, Noa Zilberman

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Internet is a complex network, comprised of thousands of interconnected Autonomous Systems. Considerable research is done in order to infer the undisclosed commercial relationships between ASes. These relationships, which have been commonly classified to four distinct Type of Relationships (ToRs), dictate the routing policies between ASes. These policies are a crucial part in understanding the Internet's traffic and behavior patterns. This work leverages Internet Point of Presence (PoP) level maps to improve AS ToR inference. We propose a method which uses PoP level maps to find complex AS relationships and detect anomalies on the AS relationship level. We present experimental results of using the method on ToR reported by CAIDA and report several types of anomalies and errors. The results demonstrate the benefits of using PoP level maps for ToR inference, requiring considerable less resources than other methods theoretically capable of detecting similar phenomena.

Original languageEnglish
Title of host publication2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013
PublisherIEEE Computer Society
Pages459-464
Number of pages6
ISBN (Print)9781479900565
DOIs
StatePublished - 2013
Event2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013 - Turin, Italy
Duration: 14 Apr 201319 Apr 2013

Publication series

Name2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013

Conference

Conference2013 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2013
Country/TerritoryItaly
CityTurin
Period14/04/1319/04/13

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