HLOC: Hints-based geolocation leveraging multiple measurement frameworks

Speaker : Maxime Mouchet
LIP6
Date: 10/11/2021
Time: 10:45 am - 12:00 pm
Location: Paris-Rennes Room (EIT Digital)

Abstract

Dear all, 

The Internet Measurement reading group will meet on Wednesday 10th.

In this session, Maxime Mouchet (Sorbonne Université, LIP6) will present HLOC: Hints-based geolocation leveraging multiple measurement frameworks  (Quirin Scheitle et al., TMA 2017).

I encourage you to join us at 10:45 for a virtual coffee break, so that the talk begins at 11:00.
https://telecom-paris.zoom.us/j/98157419805?pwd=eHNMNHZqSE1samtyUmVNRE1TZjRpdz09

Slides

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.