Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)

Method for IP geolocation based on Path Similarity

Authors
Lian-Xing Ren
Corresponding Author
Lian-Xing Ren
Available Online December 2016.
DOI
10.2991/icwcsn-16.2017.68How to use a DOI?
Keywords
IPGeolocation; measurement; delay; traceroute; path similarity; landmark
Abstract

The ability to accurately determine the geographic location of an arbitrary IP address has potential in many applications. This paper presented a novel algorithm for IP geolocating based on network measurement. Considering the features of China Internet's distribution, using trace route tools, we build database about the routing path to landmarks. Based on the database, this paper introduced GeoPath to geolocate a target quickly by path similarity. A set of landmarks with known location were tested by the proposed method and experimental results demonstrate that the method is validity and practical.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
Series
Advances in Computer Science Research
Publication Date
December 2016
ISBN
10.2991/icwcsn-16.2017.68
ISSN
2352-538X
DOI
10.2991/icwcsn-16.2017.68How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Lian-Xing Ren
PY  - 2016/12
DA  - 2016/12
TI  - Method for IP geolocation based on Path Similarity
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 315
EP  - 319
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.68
DO  - 10.2991/icwcsn-16.2017.68
ID  - Ren2016/12
ER  -