Alert Correlation & Noise Reduction
Signal over volume — incidents, not individual events
What it does
AlertMonitor's correlation engine suppresses duplicate events, groups related telemetry into single incidents, and eliminates low-confidence noise before anything reaches your analyst team. The result: your team works through incidents with clear context attached, not hundreds of individual raw alerts from the same underlying event. Alert fatigue is a choice — AlertMonitor removes it.
Alert fatigue is a security failure mode: When analysts review 200 alerts per shift, they stop reading carefully. AlertMonitor clients average 12-18 analyst-reviewed incidents per week, not per day. Every incident your analyst sees is worth their attention.
Capabilities
- Duplicate suppression: identical events from the same source deduplicated automatically
- Related event grouping: login failure + lateral movement + data access = one correlated incident
- Frequency-based suppression: known-noisy rules throttled after N occurrences per hour
- Confidence scoring: low-confidence detections enriched further before analyst escalation
- Incident timeline construction: correlated events display chronologically with causal links
- Tunable correlation windows: 5-minute, 1-hour, 24-hour correlation lookback per rule class
How it works
The correlation engine processes normalized events through a rule-based correlation layer followed by an ML-based anomaly scoring layer. Rules are maintained by the AlertMonitor security team and updated continuously with new attack patterns. The ML layer learns per-client baseline behavior over 14 days to distinguish genuine anomalies from normal operational variation. Correlation state is maintained in a streaming event processor with sub-second latency.