An investigation of geographic mapping techniques for internet hosts
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
SmartSiren: virus detection and alert for smartphones
Proceedings of the 5th international conference on Mobile systems, applications and services
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Characterizing residential broadband networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Unconstrained endpoint profiling (googling the internet)
Proceedings of the ACM SIGCOMM 2008 conference on Data communication
De-anonymizing the internet using unreliable IDs
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Volley: automated data placement for geo-distributed cloud services
NSDI'10 Proceedings of the 7th USENIX conference on Networked systems design and implementation
Detecting spammers with SNARE: spatio-temporal network-level automatic reputation engine
SSYM'09 Proceedings of the 18th conference on USENIX security symposium
A learning-based approach for IP geolocation
PAM'10 Proceedings of the 11th international conference on Passive and active measurement
Peering through the shroud: the effect of edge opacity on ip-based client identification
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Octant: a comprehensive framework for the geolocalization of internet hosts
NSDI'07 Proceedings of the 4th USENIX conference on Networked systems design & implementation
Studying inter-national mobility through IP geolocation
Proceedings of the sixth ACM international conference on Web search and data mining
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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.