Poster: GeoResolver, An Accurate, Scalable, and Explainable Geolocation Technique Using DNS Redirection

Obtaining an accurate, explainable, Internet-scale IP geolocation dataset has been a longstanding goal of the research community. Despite decades of research on IP geolocation, no current technique can provide such a dataset. In particular, latency-based geolocation techniques do not scale, because, on one hand, we have thousands of available vantage points to perform measurements, but on the other hand, we have no way to select the right ones for each IP address. In this paper, we present GeoResolver, an efficient vantage point selection methodology, based on the assumption that two IP addresses that share a similar DNS redirection are likely to be geographically close together. GeoResolver performs nearly as well as a brute force approach using all the vantage points, geolocating 94% of the targets that could actually be geolocated at metro level by using all the vantage points, while using 4.3% of the probing budget compared to a state-of-the-art technique. We carefully design GeoResolver to be both accurate and scalable and with our implementation, we start a large-scale geolocation campaign.