MNOs & Telecom Operators
LTE signalling analysis involves decoding, correlating, and visualising LTE S1/S1AP events. Real-time analysis gives mobile operators, researchers, and security teams the ability to understand how devices interact with the network, identify anomalies, and optimise operations.
Event Processing: Ingest S1AP events in real time via file, SCTP stream, TCP stream, or simulation, enabling fast and flexible analysis of signalling behaviour.
Horizon-Aware Pipeline: Correlate device activity across rolling time windows with configurable thresholds, allowing continuous visibility of mobility and signalling trends.
DSL Rules Engine: Create flexible rules for event filtering, correlation, and alerting. Support for conditional logic, including ELSE branches, enables precise monitoring and automation.
ML Anomaly Detection: Apply machine learning models—including LSTM autoencoders, movement classifiers, and isolation forests—for adaptive anomaly detection in signalling behaviour.
Dual Processing: Run rules-based and ML-based analysis in parallel to combine deterministic precision with behavioural learning.
Real-Time Inference: Sub-10ms inference ensures that anomalies and unusual patterns are surfaced instantly.
Learn / Live Modes: Train ML models on historical LTE signalling data, then deploy them in live mode to monitor events as they occur.
Interactive Dashboard: Access an intuitive web dashboard with map visualisation, area-of-interest selection, rules management, and real-time device activity tracking.
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