Anomaly Baseline Data: Anomaly baseline data refers to the statistical profiles and baselines calculated for various parameters to detect deviations indicative of potential security incidents.
Profile DB: The Profile DB is specifically designed to store such baseline data in FortiSIEM.
* Purpose: It maintains statistical profiles for different monitored parameters to facilitate anomaly detection.
* Usage: This data is used by FortiSIEM to compare real-time metrics against the established baselines to identify anomalies.
References: FortiSIEM 6.3 User Guide, Database Architecture section, which describes the different databases used in FortiSIEM and their purposes, including the Profile DB for storing anomaly baseline data.

Rule Evaluation in FortiSIEM: Rules in FortiSIEM are evaluated periodically to check if the defined conditions or subpatterns are met.
Frequency Field: The Frequency field in a rule determines the interval at which the rule's subpattern will be evaluated.
* Evaluation Interval: This defines how often the system will check the incoming events against the rule's subpattern to determine if an incident should be triggered.
* Impact on Performance: Setting an appropriate frequency is crucial to balance between timely detection of incidents and system performance.
Examples:
* If the Frequency is set to 5 minutes, the rule will evaluate the subpattern every 5 minutes.
* This means that every 5 minutes, the system will check if the conditions defined in the subpattern are met by the incoming events.
References: FortiSIEM 6.3 User Guide, Rules and Incidents section, which explains the Frequency field and how it impacts the evaluation of subpatterns in rules.