Fingerprint-Geo: IPv6 geolocation through path fingerprint

Mapping IP addresses into geographic locations is crucial for location-based services (LBS), such as online targeted ads, localized content delivery, and online account protection. However, existing methods are inaccurate in inferring the targets' locations when their network paths are incomplete. In this paper, we focus on enhancing the geolocation accuracy on IPv6 networks when targets' paths are incomplete and propose Fingerprint-Geo, an IPv6 geolocation method based on the analysis of regional path fingerprints. Each path to a target region has its unique features associated with this region, which are referred to as regional path fingerprints. By analyzing the regional path fingerprints, an overview of the network measurement characteristics in the region can be obtained, and the targets within the region can be estimated by matching fingerprints even when the paths are incomplete. Experiments conducted in ten metropolises in China and the U.S. IPv6 networks demonstrate that Fingerprint-Geo can geolocate the targets with incomplete paths and is more accurate than the typical method PBG.