Scam Bot Detection

Scams and spam are among the fastest growing threats to consumer confidence in mobile services. Fraudsters use SIM farms (large clusters of SIM cards controlled by automated systems) to create fake
accounts, send mass messages or calls, and bypass legitimate telecom services, fuelling phishing and impersonation.

Virginia Tech, in collaboration with GSMA Foundry, is leading a project to detect SIM farm activity directly
from 4G/5G network signalling. By analysing protocol level data and key performance indicators, the solution identifies abnormal patterns in real time, stopping scams before they reach consumers. The goal is to move from reactive mitigation to infrastructure level prevention, delivering safer mobile experiences
worldwide.

For consumers, the project should reduce scam calls/texts and build greater confidence in mobile services, while helping operators protect network integrity and revenue. The partners are planning to trial the solution with a North American mobile operator in 2026.

MWC26: Stopping Scams at the Source

Dr. Yaling Yang, the principal investigator and Dr. David Simpson, professor of practice in the Department of Business Information Technology, presented initial findings of this work at the MWC26 Barcelona. The live demo at Pavilion booth and the roundtable helped attendees gain insights into how digital twin environments can model SIM farm operations and measure fraud detection accuracy.