# Passport: Enabling Accurate Country-Level Router Geolocation using Inaccurate Sources

## TL;DR

Passport is a novel system that accurately determines the country-level location of routers in internet paths using limited measurements and machine learning, addressing a critical gap in geolocation tools.

## Contribution

It introduces a new approach combining multiple data sources with machine learning for precise router geolocation at the country level.

## Key findings

- Passport outperforms existing geolocation techniques.
- It identifies cases where internet paths cross multiple countries.
- The system has implications for security, privacy, and performance.

## Abstract

When does Internet traffic cross international borders? This question has major geopolitical, legal and social implications and is surprisingly difficult to answer. A critical stumbling block is a dearth of tools that accurately map routers traversed by Internet traffic to the countries in which they are located. This paper presents Passport: a new approach for efficient, accurate country-level router geolocation and a system that implements it. Passport provides location predictions with limited active measurements, using machine learning to combine information from IP geolocation databases, router hostnames, whois records, and ping measurements. We show that Passport substantially outperforms existing techniques, and identify cases where paths traverse countries with implications for security, privacy, and performance.