Mobile Network Fraud Detection via Real-Time Signaling Interception
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Solution Overview
Problem
Current methods for detecting fraudulent activity in mobile telephony networks are ineffective as they only identify fraudulent behavior after the communication has completed, allowing losses to occur before intervention is possible.
Innovation Solution
A mobile communications fraud detection system with probe devices intercepting data across various interfaces in the network to analyze real-time data, including user identities, message content, and signaling tones, enabling the detection of fraudulent activities such as gateway fraud, revenue share fraud, credit card fraud, spam, and malware, while ensuring data protection through anonymization and encryption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If billing data analysis is used to detect fraudulent activity, then fraud detection capability is provided, but detection occurs only after communication completion causing loss of intervention opportunity
Solution Approach 1:
The system performs preliminary actions by intercepting and analyzing signaling data during the communication process itself, rather than waiting for billing data generation. Probe devices capture data at multiple network interfaces (A-interface, Gb-interface, lu-CS interface, lu-PS interface) in real-time, enabling fraud detection before the communication completes and losses occur.
2Speed
If probe devices intercept data at multiple network interfaces, then real-time fraud detection is enabled, but system complexity increases
Solution Approach 1:
The system segments the fraud detection function into separate probe devices deployed at different network interfaces (A-interface between MSC and GGSN, Gb-interface between BSC and SGSN, lu-CS interface between RNC and MSC, lu-PS interface between RNC and SGSN). Each probe device independently intercepts and analyzes signaling data at its specific interface, distributing the detection workload and reducing individual device complexity while maintaining real-time detection capability across the entire network.
Data Source
AI summary
A mobile communications fraud detection system is provided in which one or more probe devices are deployed to intercept predetermined types of data being carried over selected interfaces within the mobile communications network. In particular, the probe devices are arranged to intercept data being carried between equipment responsible for providing the air interface to mobile communications devices using the network and equipment interfacing with the mobile network's core switching equipment. Fraudulent activity relating to gateway fraud, revenue sharing fraud, credit or debit card fraud, spam generation and fraudulent or other activity indicative of the presence of malware executing on a mobile communications device.