- Reduced time to detect
- Ability to tear down fraudulent calls before it occurs
- Deterministic alarms using signaling fields that aren’t present in CDRs
- Reduction in decision-time of analysts
Why detect Fraud using Signaling Methods?
Real-time vigilance to prevent fraud and security attacks
The Signaling Security solution is designed to analyze real-time network traffic to address traditional and new-age risks across various services. It monitors multiple parts of a telco network, starting at the IP layer and going up to the application layer to detect fraud and security breaches. By starting at the lower level of the network stack, you can now detect attacks earlier than traditional detection methods that are dependent on XDRs to be generated. The use of advanced detection techniques such as machine learning and a vast dictionary of detection elements coupled with the ability to tear down an attack as it is being set up allow fraud and security teams to get ahead of a potential revenue loss event.
Our solution has access to 58,400 unique threat intelligence signatures drawn in real-time from the largest honeypot network in the world.
Over 3000 pre-configured rules to detect known attacks and reduce fraud run-time significantly.
Custom-built algorithms that leverage supervised and unsupervised models to detect specific attack types.
The whitepaper focuses on the sale of handsets/devices, fraud associated with handset sales, and the must-have capabilities in an anti-fraud solution.
Tackling Frauds in Mobile Money Ecosystem: A Case Study of MTN Eswatini