NDSS2017
FBS-Radar: Uncovering Fake Base Stations at Scale in the Wild
Zhenhua Li, Weiwei Wang, Christo Wilson, Jian Chen, Chen Qian, Taeho Jung, Lan Zhang, Kebin Liu, Xiangyang Li, Yunhao Liu
92 citations
Abstract
Base stations constitute the basic infrastructure of today's cellular networks. Unfortunately, vulnerabilities in the GSM (2G) network protocol enable the creation of fake base stations (FBSes) that are not authorized by network operators. Criminal gangs are using FBSes to directly attack users by sending spam and fraud SMS messages, even if the users have access to 3G/4G networks. In this paper, we present the design, deployment, and evolution of an FBS detection system called FBS-Radar, based on crowdsourced data of nearly 100M users. In particular, we evaluate five different metrics for identifying FBSes in the wild, and find that FBSes can be precisely identified without sacrificing user privacy. Additionally, we present a novel method for accurately geolocating FBSes while incurring negligible impact on end-user devices. Our system protects users from millions of spam and fraud SMS messages per day, and has helped the authorities arrest hundreds of FBS operators. Permission to freely reproduce all or part of this paper for noncommercial purposes is granted provided that copies bear this notice and the full citation on the first page. Reproduction for commercial purposes is strictly prohibited without the prior written consent of the Internet Society, the first-named author (for reproduction of an entire paper only), and the author's employer if the paper was prepared within the scope of employment.