For what type of data values does the rule engine query the profile database?
Answer(s): D
FortiSIEM's rule engine queries the profile database to analyze historical behavior and detect anomalies. The profile database stores statistical baselines, which include:Statistical average (mean values over time)Standard deviation (variability from the mean)These values help the rule engine determine whether an observed metric (such as logins, failed attempts, network traffic, or system performance) deviates significantly from the normal pattern for the same hour of the day.
Which organization do agents belong to after registration? (Choose two.)
Answer(s): B,D
When registering agents in FortiSIEM, the organization to which they belong depends on how they are installed:Windows AgentsDuring installation, the setup wizard prompts the user to specify the organization. This ensures the agent is correctly assigned to the organization defined during setup.Linux AgentsInstallation on Linux requires command-line parameters, including the organization name. This means that the organization is explicitly defined during the installation process.
What is the hourly bucket used in baselining?
In FortiSIEM baselining, an hourly bucket is used to maintain hourly-specific statistical baselines. This helps detect anomalies by comparing current activity against historical norms for each hour of the day, separately for weekdays and weekends.The system maintains hourly profiles, ensuring that anomalies are detected based on similar timeframes. This approach prevents false positives due to natural variations in network activity across different times of the day and different days of the week.
What are two functions of numpoints in a rule and profile database? (Choose two.)
Answer(s): A,C
In FortiSIEM, numPoints is a parameter used in rules and the profile database to ensure the reliability of statistical baselines and prevent anomalies from being falsely triggered due to insufficient data.1. To prevent premature triggering of a rule before a baseline is set and becomes active. numPoints ensures that a rule does not trigger until a sufficient number of data points are collected for the baseline.Without enough data, the system may generate false positives due to the lack of a stable historical pattern.2. To fetch only values from the profile database that have numPoints greater than a certain threshold.When querying the profile database, numPoints acts as a filter to ensure that only data points meeting a minimum threshold are considered for analysis. This prevents unreliable or insufficient historical data from affecting anomaly detection.
Refer to the exhibit.Consider the five account locked events received by FortiSIEM from domain controllers within the last 10 minutes (ten minutes is the evaluation window for the subpattern DomainAcctLockout):If you look for one or more matching events and groupings by the same reporting IP address, reporting device, and user, how many incidents are created?
Answer(s): C
The rule groups events by Reporting IP, Reporting Device, and User. Let's analyze the five events:Events Received:1. Reporting IP: 1.1.1.1, Reporting Device: Server101, User: John2. Reporting IP: 1.1.1.1, Reporting Device: Server101, User: Craig3. Reporting IP: 1.1.1.2, Reporting Device: Server109, User: Mary4. Reporting IP: 1.1.1.1, Reporting Device: Server101, User: Craig (Duplicate of #2)5. Reporting IP: 1.1.1.1, Reporting Device: Server101, User: John (Duplicate of #1) Grouping Based on:Reporting IPReporting DeviceUserCount unique groups:1. (1.1.1.1, Server101, John) 2 occurrences (counted as one group)2. (1.1.1.1, Server101, Craig) 2 occurrences (counted as one group)3. (1.1.1.2, Server109, Mary) 1 occurrence (counted as one group) Since we need at least one matching event (count >= 1) per group, incidents are created for each unique group.Total unique groups (incidents created) = 2John on Server101 (1.1.1.1)Craig on Server101 (1.1.1.1)
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