Anomaly detection API for identifying UAVs/drones in LTE/5G networks.
CellSentinel by Melrose Networks is a real-time, enterprise‑grade LTE S1AP and 5G NGAP analysis service utilising advanced machine learning to monitor, analyse, and detect threats across 4G and 5G networks. Built to specialise in drone/UAV detection, it learns your network’s normal handover patterns from S1AP and flags abnormal cell‑to‑cell transitions with explainable scores, while supporting comprehensive LTE and 5G signaling analysis through deep inspection of protocol messages. Delivered on a hardened stack with JWT/API‑key security and OpenAPI documentation, CellSentinel deploys easily on‑prem or in the cloud and integrates seamlessly with existing NOC/SIEM workflows.
Advanced ensemble learning models automatically detect anomalous behavior patterns and classify movement types across mobile networks.
Process thousands of protocol events per second with microsecond latency for comprehensive network-wide monitoring and analysis.
Complete programmatic access for seamless integration with existing security and network operations systems.
Supports multiple deployment patterns from standalone installations to distributed cloud-native architectures for diverse environments.
CellSentinel incorporates sophisticated machine learning capabilities to automatically detect anomalous behavior patterns in cellular networks. The ML subsystem combines multiple complementary approaches to deliver intelligent, real-time threat detection and behavioral analysis.
Speed, distance, direction, and trajectory analysis
Timing patterns, duration analysis, and activity schedules
Handover patterns, cell transitions, and geographic coverage
Cross-border activity, movement linearity, and behavioral fingerprinting
