SigN: SIMBox Activity Detection Through Latency Anomalies at the Cellular Edge
Anne Josiane Kouam, Aline Carneiro Viana (TRiBE), Philippe Martins, (INFRES), Cedric Adjih (TRiBE), Alain Tchana (Grenoble INP)

TL;DR
SigN is a new method that detects SIMBox fraud in cellular networks by analyzing latency anomalies during device attachment, effectively identifying malicious devices with high accuracy and robustness.
Contribution
Introduces SigN, a novel latency-based detection technique for SIMBox devices at the cellular edge, addressing limitations of existing methods and enhancing practical deployment.
Findings
SIMBox devices cause significantly higher attachment latencies.
Latency during authentication can be up to 23 times higher for SIMBox.
The method is effective in both indoor and outdoor environments.
Abstract
Despite their widespread adoption, cellular networks face growing vulnerabilities due to their inherent complexity and the integration of advanced technologies. One of the major threats in this landscape is Voice over IP (VoIP) to GSM gateways, known as SIMBox devices. These devices use multiple SIM cards to route VoIP traffic through cellular networks, enabling international bypass fraud with losses of up to $3.11 billion annually. Beyond financial impact, SIMBox activity degrades network performance, threatens national security, and facilitates eavesdropping on communications. Existing detection methods for SIMBox activity are hindered by evolving fraud techniques and implementation complexities, limiting their practical adoption in operator networks.This paper addresses the limitations of current detection methods by introducing SigN , a novel approach to identifying SIMBox activity…
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Taxonomy
TopicsIPv6, Mobility, Handover, Networks, Security · Internet Traffic Analysis and Secure E-voting · Advanced Authentication Protocols Security
