IP-geolocater: a more reliable IP geolocation algorithm based on router error training

Abstract

Location based services (LBS) are widely utilized, and determining the location of users’ IP is the foundation for LBS. Constrained by unstable delay and insufficient landmarks, the existing geolocation algorithms have problems such as low geolocation accuracy and uncertain geolocation error, difficult to meet the requirements of LBS for accuracy and reliability. A new IP geolocation algorithm based on router error training is proposed in this manuscript to improve the accuracy of geolocation results and obtain the current geolocation error range. Firstly, bootstrapping is utilized to divide the landmark data into training set and verification set, and /24 subnet distribution is utilized to extend the training set. Secondly, the path detection is performed on nodes in the three data sets respectively to extract the metropolitan area network (MAN) of the target city, and the geolocation result and error of each router in MAN are obtained by training the detection results. Finally, the MAN is utilized to get the target’s location. Based on China’s 24,254 IP geolocation experiments, the proposed algorithm has higher geolocation accuracy and lower median error than existing typical geolocation algorithms LBG, SLG, NNG and RNBG, and in most cases the difference is less than 10km between estimated error and actual error.

Keywords

estimated error / geolocation / path detection / network measurement

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