Detecting IMSI-Catchers by Characterizing Identity Exposing Messages in Cellular Traffic


METADATA ONLY
Loading...

Date

2025-02

Publication Type

Conference Paper

ETH Bibliography

yes

Citations

Altmetric
METADATA ONLY

Data

Rights / License

Abstract

IMSI-Catchers allow parties other than cellular network providers to covertly track mobile device users. While the research community has developed many tools to combat this problem, current solutions focus on correlated behavior and are therefore subject to substantial false classifications. In this paper, we present a standards-driven methodology that focuses on the messages an IMSI-Catcher textit{must} use to cause mobile devices to provide their permanent identifiers. That is, our approach focuses on causal attributes rather than correlated ones. We systematically analyze message flows that would lead to IMSI exposure (most of which have not been previously considered in the research community), and identify 53 messages an IMSI-Catcher can use for its attack. We then perform a measurement study on two continents to characterize the ratio in which connections use these messages in normal operations. We use these benchmarks to compare against open-source IMSI-Catcher implementations and then observe anomalous behavior at a large-scale event with significant media attention. Our analysis strongly implies the presence of an IMSI-Catcher at said public event ($p << 0.005$), thus representing the first publication to provide evidence of the statistical significance of its findings.

Publication status

published

Editor

Book title

Network and Distributed System Security (NDSS) Symposium 2025

Journal / series

Volume

Pages / Article No.

1115

Publisher

Internet Society

Event

32nd Network and Distributed System Security Symposium (NDSS 2025)

Edition / version

Methods

Software

Geographic location

Date collected

Date created

Subject

Organisational unit

03755 - Capkun, Srdan / Capkun, Srdan check_circle

Notes

Conference lecture held on February 25, 2025.

Funding

Related publications and datasets