Adaptive IP geolocation framework for target network scenarios

The target location can be determined through IP geolocation, serving as a vital foundation for location-based services.Researchers have proposed various IP geolocation algorithms with different implementation principles to cater to different network scenarios.However, maintaining an ideal geolocati...

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Bibliographic Details
Main Author: Shuodi ZU, Shichang DING, Fuxiang YUAN, Xiangyang LUO
Format: Article
Language:English
Published: POSTS&TELECOM PRESS Co., LTD 2023-12-01
Series:网络与信息安全学报
Subjects:
Online Access:https://www.infocomm-journal.com/cjnis/CN/10.11959/j.issn.2096-109x.2023084
Description
Summary:The target location can be determined through IP geolocation, serving as a vital foundation for location-based services.Researchers have proposed various IP geolocation algorithms with different implementation principles to cater to different network scenarios.However, maintaining an ideal geolocation effect proves challenging for these algorithms in diverse network scenarios.Three typical implementation principles for IP geolocation based on network measurement were introduced.The advantages and disadvantages of these methods in various network scenarios were analyzed, and an adaptive IP geolocation framework specifically tailored to target network scenarios was proposed.The geolocation framework was functioned as follows: initially, a preliminary city-level location estimation was obtained by comparing the target’s location with the landmark database.Then, detection sources were deployed in a distributed manner, and information such as delay, topology and same subnet landmarks for the target city was gathered to determine the network scenario.Finally, an appropriate geolocation method was employed to accurately estimate the target’s location according to the identified network scenario.Through simulation geolocation experiments in 11 cities of China, the multi-level performance of various IP geolocation methods supported by landmark data of different quantities and distributions was evaluated.The results indicate that the proposed framework achieves a city-level geolocation success rate of 96.16% and a median error of 4.13 km for street-level geolocation.Moreover, the framework demonstrates stable geolocation performance across different conditions, including varying same subnet landmark numbers and target accessibility.These experimental findings validate the effectiveness of the proposed framework and offer novel insights for IP geolocation research.
ISSN:2096-109X