Abstract: An anomaly detection method and system determine network status by monitoring network activity. A statistics based profile for said network over a period is generated to analyze potentially anomalous network activity to determine if said network activity is anomalous by comparing current activity against the profile. Using the profile as a reference, the anomaly detection system and process estimate and prioritize potentially anomalous network activity based on the probability that the behavior is anomalous. The level of severity that the anomaly detection process uses to determine if an alarm is needed is based on comparing user-adjustable thresholds to the current probability. If the threshold has been breached, the user is alerted, subject to other quality checks. After a reporting cycle concludes, the anomaly detection system and process recompiles the statistics based profile to take into account the information observed in the previous reporting cycle.

Abstract: An anomaly detection method and system determine network status by monitoring network activity. A statistics based profile for said network over a period is generated to analyze potentially anomalous network activity to determine if said network activity is anomalous by comparing current activity against the profile. Using the profile as a reference, the anomaly detection system and process estimate and prioritize potentially anomalous network activity based on the probability that the behavior is anomalous. The level of severity that the anomaly detection process uses to determine if an alarm is needed is based on comparing user-adjustable thresholds to the current probability. If the threshold has been breached, the user is alerted, subject to other quality checks. After a reporting cycle concludes, the anomaly detection system and process recompiles the statistics based profile to take into account the information observed in the previous reporting cycle.