How to Tell an Airport from a Home: Techniques and Applications

Andreas Pitsillidis, Yinglian Xie, Fang Yu, Martin Abadi, Geofferey M. Voelker, and Stefan Savage

Abstract

Today’s Internet services increasingly use IP-based geolocation

to specialize the content and service provisioning for

each user. However, these systems focus almost exclusively

on the current position of users and do not attempt to infer or

exploit any qualitative context about the location’s relationship

with the user (e.g., is the user at home? on a business

trip?). This paper develops such a context by profiling the

usage patterns of IP address ranges, relying on known user

and machine identifiers to track accesses over time. Our preliminary

results suggest that rough location categories such

as residences, workplaces, and travel venues can be accurately

inferred, enabling a range of potential applications

from demographic analyses to ad specialization and security improvements

Details

Publication typeProceedings
Published inHotNets 2010
PublisherAssociation for Computing Machinery, Inc.
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