ONE-Geo: Client-Independent IP Geolocation Based on Owner Name Extraction

Client-independent Internet Protocol address (IP) geolocation is a critical problem in the Internet World, of which the accuracy is based on highly reliable landmarks. However, most existing methods focus heavily on improving the location estimating method rather than improving the quality and quantity of landmarks. Without sufficient landmarks of high quality, they face difficulties when attempting to further improve accuracy. Even though some existing mining based methods dig massive landmarks from online web resources, most landmarks are of low quality because they do not make full use of these open resources. In this paper, we propose ONE-Geo, a methodology to mine highly reliable landmarks as much as possible by extracting the owner name of web servers. For a given target IP, ONE-Geo extracts the real owner name from web page information and registration records. Utilizing this clue, ONE-Geo determines the correct location by searching address information on an organization knowledge graph and conduct inference. Experimental results show that ONE-Geo achieves a median error distance of 463 m on 165 web servers and a median error distance of 7.7 km on 721 nodes that do not host a website. For web servers, ONE-Geo outperforms existing methods and several commercial tools. To be specific, 66.1% nodes are geolocated by ONE-Geo with an error less than 1 km, which is two times as many as Street-level Geolocation(SLG), which is one of the best existing methods on IP geolocating.

[1]  Brian D. Davison,et al.  Improving IP Geolocation using Query Logs , 2016, WSDM '16.

[2]  David Wetherall,et al.  Towards IP geolocation using delay and topology measurements , 2006, IMC '06.

[3]  Nick Feamster,et al.  Geographic locality of IP prefixes , 2005, IMC '05.

[4]  Hao Jiang,et al.  IP geolocation estimation using neural networks with stable landmarks , 2016, 2016 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS).

[5]  Curtis R. Taylor,et al.  From an IP Address to a Street Address: Using Wireless Signals to Locate a Target , 2013, WOOT.

[6]  T. Vincenty.  DIRECT AND INVERSE SOLUTIONS OF GEODESICS ON THE ELLIPSOID WITH APPLICATION OF NESTED EQUATIONS , 1975 .

[7]  Paul Barford,et al.  A Learning-Based Approach for IP Geolocation , 2010, PAM.

[8]  Alessio Vecchio,et al.  Smartphone-based geolocation of Internet hosts , 2017, Comput. Networks.

[9]  Aleksandar Kuzmanovic,et al.  Towards Street-Level Client-Independent IP Geolocation , 2011, NSDI.

[10]  Georg Carle,et al.  HLOC: Hints-based geolocation leveraging multiple measurement frameworks , 2017, 2017 Network Traffic Measurement and Analysis Conference (TMA).

[11]  Kimberly C. Claffy,et al.  DRoP: DNS-based router positioning , 2014, CCRV.

[12]  K. K. Ramakrishnan,et al.  Mining checkins from location-sharing services for client-independent IP geolocation , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[13]  Serge Fdida,et al.  Constraint-based geolocation of internet hosts , 2006, TNET.

[14]  Emin Gün Sirer,et al.  Octant: A Comprehensive Framework for the Geolocalization of Internet Hosts , 2007, NSDI.

[15]  Helen J. Wang,et al.  Mining the Web and the Internet for Accurate IP Address Geolocations , 2009, IEEE INFOCOM 2009.

[16]  Lakshminarayanan Subramanian,et al.  An investigation of geographic mapping techniques for internet hosts , 2001, SIGCOMM 2001.