Geolocating a WeChat user based on the relation between reported and actual distance - Wenqi Shi; Xiangyang Luo; Fan Zhao; Ziru Peng; Qingfeng Cheng; Yong Gan (International Journal of Distributed Sensor Networks)
The combination of social networks and the Internet of Things has raised a new wave of network technology application. However, the presence of malicious social network users poses a potential threat to Internet of Things security, and the research on social network user geolocation technology is of great significance. The accuracy of existing geolocation methods for WeChat users depends on the stable correspondence between the reported distance and actual distance. In view of the difficulty to pinpoint users’ location in the real world due to WeChat location protection strategy, a WeChat user geolocation algorithm based on the reported and actual distance relation analysis is proposed. The proposed algorithm selects the target reported distance and determines the initial target space based on statistical characteristics of the relation between the reported distance and actual distance. What is more, stepwise strategies are taken to improve the accuracy rate of space partition. Experimental results show that, on the premise that target users can be discovered, the proposed algorithm could achieve higher accuracy compared with the classical space partition–based algorithm and the heuristic number theory based algorithm. The highest geolocation accuracy is within 10 m and 56% of geolocation results are within 60 m.