IP Geolocation through Reverse DNS

TL;DR

This paper presents a machine learning-based method for IP geolocation using reverse DNS hostnames, significantly improving accuracy over academic baselines and complementing commercial databases.

Contribution

It introduces a novel approach leveraging publicly accessible reverse DNS data, enhancing IP geolocation accuracy and compatibility with existing methods.

Findings

Outperforms academic geolocation baselines

Complementary to commercial geolocation databases

Open-sourced for reproducibility

Abstract

IP Geolocation databases are widely used in online services to map end user IP addresses to their geographical locations. However, they use proprietary geolocation methods and in some cases they have poor accuracy. We propose a systematic approach to use publicly accessible reverse DNS hostnames for geolocating IP addresses. Our method is designed to be combined with other geolocation data sources. We cast the task as a machine learning problem where for a given hostname, we generate and rank a list of potential location candidates. We evaluate our approach against three state of the art academic baselines and two state of the art commercial IP geolocation databases. We show that our work significantly outperforms the academic baselines, and is complementary and competitive with commercial databases. To aid reproducibility, we open source our entire approach.