Byeongdo Hong (The Affiliated Institute of ETRI), Gunwoo Yoon (The Affiliated Institute of ETRI)

LTE networks employ Globally Unique Temporary Identifiers (GUTIs) to shield subscribers from permanent International Mobile Subscriber Identity (IMSI) exposure, yet we show that these identifiers can be resolved and linked to specific devices through passive observation without prior knowledge of targets. We correlate time-stamped visual observations of device use with over-the-air control-plane messages captured using commodity Software-Defined Radios (SDRs). A Finite-State-Machine (FSM) algorithm processes the synchronized streams to resolve each device's GUTI within the camera's Field of View (FoV), requiring as few as three observed user interactions when the corresponding control-plane messages are captured.

Field experiments across multiple commercial Long-Term Evolution (LTE) networks validate multi-target resolution: In some deployments, we observed GUTIs persisting for up to 33 days, with reassignment behaviors that were often linkable. Once linked, these long-lived identifiers enable hierarchical location tracking—from cell to paging-area scale—by passively monitoring paging and Radio Resource Control (RRC) messages. Unlike active IMSI catchers or prior GUTI attacks that require pre-existing identifiers (e.g., phone numbers) and active probing, our approach is listen-only and scales to multiple devices within view.

View More Papers

Automating Firmware Vulnerability Triage via High-Level Representations and Similarity...

Daniel Huici, Ricardo J. Rodríguez (University of Zaragoza), Andrei Costin (University of Jyvaskyla), Narges Yousefnezhad (Binare Oy)

Read More

A Unified Defense Framework Against Membership Inference in Federated...

Liwei Zhang (Beijing University of Posts and Telecommunications), Linghui Li (Beijing University of Posts and Telecommunications), Xiaotian Si (Beijing University of Posts and Telecommunications), Ziduo Guo (Beijing University of Posts and Telecommunications), Xingwu Wang (Beijing University of Posts and Telecommunications), Kaiguo Yuan (Beijing University of Posts and Telecommunications), Bingyu Li (School of Cyber Science and…

Read More

MUTATO: Enhancing Fuzz Drivers with Adaptive API Option Mutation

Shuangxiang Kan (University of New South Wales), Xiao Cheng (Macquarie University), Yuekang Li (University of New South Wales)

Read More