Mobile IP Geolocation Based on District Anchor Without Cooperation of Users or Internet Service Providers

• Published in: IEEE/ACM transactions on networking 2024-10, p.1-17
• Main Authors: Li, Ruixiang, Yuan, Xiaoyun, Yin, Meijuan, Luo, Xiangyang
• Format: Article
• Language: English
• Subjects: cellular network; Clustering algorithms; Data mining; Delays; District anchor; Geology; IP networks; Mobile handsets; mobile IP geolocation; Probes; Reliability; two-stages clustering; Urban areas
• ISSN: 1063-6692; 1558-2566
• DOI: 10.1109/TNET.2024.3471335

Mobile IP geolocation aims to obtain a mobile device's geographic location by IP. This technology is widely used in preventing financial risk, investigating cybercrime, and delivering targeted information. Currently, there are three types of IP geolocation: based on cooperation, querying in database, or network measurement. However, since restricted cooperation, low-reliability databases, and unresponsive mobile IPs, existing technologies are hard to geolocate fine-grained location of mobile IP. In this paper, we propose the concept of district anchor, and propose a non-cooperative mobile IP geolocation scheme, including three parts: acquiring district anchors by clustering, evaluating the reliability of district anchors, and geolocating mobile IPs. We also give implemented approach of this scheme. Instead of using existing clustering algorithms treating IPs and geolocations in no particular order, we propose two-stages clustering algorithm (IPG2C) to acquire district anchors, and establish reliability evaluation mechanism by IP distribution and spatial distribution of cluster. Eventually, using obtained reliable district anchors, we use "subnet geolocation" strategy to geolocate mobile IPs. The experimental results in 10 cities show that: 1) our scheme can be used to geolocate mobile IPs without cooperation; 2) the mean geolocation error is 12.47km, where precision of 56.67% of mobile IPs is street-level and minimum error is only 13m; 3) that the mean geolocation error of the anchor-based method is smaller than that of the landmark-based method; 4) compared with 13 clustering algorithms (e.g., K-Means ++ , Mean Shift, DBSCAN, and GMM), mean geolocation error using IPG2C's district anchors is reduced by 26.62% \sim 50.77%.