Scam Bot Virginia Tech Foundry Roundtable

Session description:

SIM farms, large-scale clusters of SIM cards used to automate scams, account takeovers, and other large-volume fraud, are causing growing harm to consumers and threatening the security and reliability of mobile networks worldwide. To counter this growing challenge, Virginia Tech, in collaboration with GSMA Foundry, is pioneering a new research approach that combines telecom network simulation, AI, and security innovation.

This session will reveal progress from the SIM Farm Detection Initiative, a joint effort led by Virginia Tech’s Brain Inspired Computing, Communication, and Security (BRICCS) center. The project leverages a high-fidelity cellular network digital twin to model real-world RAN and core network behavior, simulate large-scale automation patterns, and safely develop AI-driven detection methods.

Attendees will gain insights into:

• How digital twin environments can model SIM farm operations and measure fraud detection accuracy

• The early identification of key RAN and signaling KPIs that serve as indicators of automated or coordinated SIM farm activity

• The design of machine learning–based classifiers that detect abnormal session behaviors and cross-SIM correlations under realistic network conditions

By combining the digital twin environment with AI-driven detection models, the initiative enables researchers and operators to simulate SIM farm attacks and test countermeasures in realistic network conditions, helping strengthen network protection and consumer trust without impacting live systems.

Speakers:

•        Prof. Yaling Yang, Director, BRICCS, Virginia Tech

•        Prof. David Simpson, Virginia Tech