HLOC: Hints-based geolocation leveraging multiple measurement frameworks

Quirin Scheitle, Oliver Gasser, Patrick Sattler, Georg Carle

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

38 Zitate (Scopus)

Abstract

Geographically locating an IP address is of interest for many purposes. There are two major ways to obtain the location of an IP address: querying commercial databases or conducting latency measurements. For structural Internet nodes, such as routers, commercial databases are limited by low accuracy, while current measurement-based approaches overwhelm users with setup overhead and scalability issues. In this work we present our system HLOC, aiming to combine the ease of database use with the accuracy of latency measurements. We evaluate HLOC on a comprehensive router data set of 1.4M IPv4 and 183k IPv6 routers. HLOC first extracts location hints from rDNS names, and then conducts multi-tier latency measurements. Configuration complexity is minimized by using publicly available large-scale measurement frameworks such as RIPE Atlas. Using this measurement, we can confirm or disprove the location hints found in domain names. We publicly release HLOC's ready-to-use source code, enabling researchers to easily increase geolocation accuracy with minimum overhead.

OriginalspracheEnglisch
TitelTMA 2017 - Proceedings of the 1st Network Traffic Measurement and Analysis Conference
Herausgeber (Verlag)Institute of Electrical and Electronics Engineers Inc.
ISBN (elektronisch)9783901882951
DOIs
PublikationsstatusVeröffentlicht - 4 Aug. 2017
Veranstaltung1st Network Traffic Measurement and Analysis Conference, TMA 2017 - Dublin, Irland
Dauer: 21 Juni 201723 Juni 2017

Publikationsreihe

NameTMA 2017 - Proceedings of the 1st Network Traffic Measurement and Analysis Conference

Konferenz

Konferenz1st Network Traffic Measurement and Analysis Conference, TMA 2017
Land/GebietIrland
OrtDublin
Zeitraum21/06/1723/06/17

Fingerprint

Untersuchen Sie die Forschungsthemen von „HLOC: Hints-based geolocation leveraging multiple measurement frameworks“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren