Where Are WeChat Users
A Geolocation Method Based on User Missequence State Analysis
Bibliographic Data
| ID | 22108173 |
|---|---|
| Authors | Wenqi Shi (0000-0001-8972-7342, PLA Information Engineering University), Xiangyang Luo (0000-0001-6062-2950, PLA Information Engineering University), Jiadong Guo (0000-0002-1498-2194, PLA Information Engineering University), Chong Liu (0009-0007-7425-8847, PLA Information Engineering University), Fenlin Liu (0000-0001-8019-1713, PLA Information Engineering University) |
| Year | 2021 |
| Volume | 8 |
| Issue | 2 |
| Pages | 319-331 |
| Publication date | 2021-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | IEEE Transactions on Computational Social Systems (JOURNAL) |
| Journal identifiers | ISSN: 2329-924X • E-ISSN: 2373-7476 |
| Publisher | Institute of Electrical and Electronics Engineers (IEEE) (PUBLISHER) |
| DOI | 10.1109/tcss.2021.3049120 |
| OpenAlex | W3122074088 |
| Language | EN |
| References cited | 18 |
WeChat has earned more than one billion users worldwide. Research on the geolocation of WeChat users can not only discover the location of malicious users but also verify the validity of user privacy protection strategies. However, existing methods are susceptible to WeChat's location confusion strategies, resulting in intolerable geolocating errors. In this article, a WeChat user geolocation method based on user missequence state analysis (MSAG) is proposed. Different from the existing methods which usually rely on the relationship between reported and actual distances of nearby users, MSAG utilizes the relation between user order and actual distances to geolocate the target. By statistical analysis of sequence changes of nearby users under different actual distances, the distance range that causes nearby users missequence is determined. During geolocation, the distance range of the target is delimited by checking the missequence state of the target and a user with a known location. Finally, we discuss trilateration strategies for different abnormal situations. Experimental results show that MASG can achieve high-precision geolocation of WeChat users, the average error is less than 50 m, and 72% of geolocating errors are within 60 m; compared with existing typical algorithms, the average error is reduced by 23.7%-50.7
Confusion · Data mining · Geolocation · Real-time computing · Trilateration · World Wide Web · Caching and Content Delivery · Computer Science · Engineering · Human Mobility and Location-Based Analysis · Opportunistic and Delay-Tolerant Networks
| Highly cited | No |
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