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| Section | Objectives |
|---|---|
| FortiEDR and Security Policy Integration | - FortiEDR Security Configuration
|
| Advanced Analytics and Integrations | - ML, UEBA, and ZTNA
|
| Analytics and Search | - Query and Event Analysis
|
| Rules and Incident Management | - Rules and Alerts
|
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NEW QUESTION # 82
Refer to the exhibit.
Which section contains the subpattern configuration that determines how many matching events are needed to trigger the rule?
Answer: B
Explanation:
The Aggregate section contains the condition COUNT(Matched Events) > = 1, which defines how many events must match the filter criteria for the rule to trigger. This is the subpattern configuration that determines the event threshold.
The correct answer is A. Aggregate . In FortiSIEM rule subpatterns, the Filter section defines which events are eligible for matching, but the Aggregate section defines the statistical or threshold condition that must be satisfied before the subpattern is considered matched. The Study Guide explains that rule conditions are built from subpatterns of event attribute filters and aggregation functions. It also states that a single-subpattern rule is formed by three fields: filters, aggregate, and group by. In the exhibit, the aggregate line is COUNT (Matched Events) > = 1. That expression directly specifies the number of matching events required to satisfy the subpattern. Group By only controls how matching events are partitioned into separate evaluation groups.
Actions define what happens after a rule triggers, such as incident generation or notification. Filters define the event type or attribute criteria, but they do not define the required count threshold. Therefore, the section that determines how many matching events are needed is the Aggregate section.
NEW QUESTION # 83
Which run mode takes the most time to perform machine learning tasks?
Answer: A
Explanation:
The correct answer is Local Auto. The uploaded answer was right, but its explanation was sloppy because it incorrectly described Local mode as the most time-consuming mode. In FortiSIEM machine learning, Local Auto mode selects the best algorithm by evaluating multiple candidate algorithms. The User Guide states that in Local Auto mode, "FortiSIEM picks the best algorithm" and that the Max Run Time parameter limits how long the job can run; longer runtime can produce better results. That is why Local Auto can take the most time. Forecasting and Regression are task types, not run modes.
NEW QUESTION # 84
How can you query the configuration management database (CMDB) in an analytics search?
Answer: C
Explanation:
The correct answer is A because CMDB objects are referenced from the Value field after selecting the appropriate event attribute and operator. The FortiSIEM Study Guide gives a structured search example that references the CMDB. In that example, the attribute is Reporting IP, the operator is IN, and the value is selected from CMDB groups such as Devices: Windows and Networks: Inside Net. The guide explains that to show events reported by Windows servers within a specific network, you set the attribute and operator first, then browse the CMDB and select the relevant CMDB group value. This confirms the workflow: the CMDB reference is chosen as the value of the condition, not as the attribute itself. Option B is incorrect because the CMDB tab is not used to launch the analytics search this way.
Option C is not a valid workflow. Option D is wrong because the attribute is selected from event or CMDB attribute lists, while the CMDB object or group is selected in the value field.
NEW QUESTION # 85
Which two data areas can you use for user and entity behavior analytics (EBA) machine learning models?
(Choose two.)
Answer: A,D
Explanation:
The correct answers are A. Process and C. Resources. FortiSIEM UEBA/EBA analytics uses endpoint and behavior-related telemetry to identify abnormal activity. The Study Guide explains that the UEBA incident dashboard shows incidents that the AI module creates based on alerts received from FortiInsight. The UEBA attribute list includes the incident name, host, application, user, tag, and activity. This aligns with process-oriented activity monitoring from endpoint agents. The performance and baseline lessons also explain that FortiSIEM collects performance and availability data from devices and applications, including resource-utilization metrics, and uses that information to build baselines and detect anomalous activity. Resource behavior includes CPU, memory, disk, I/O, and similar utilization patterns, which are valid behavioral-model inputs. Location and Network are important FortiSIEM context areas, but in this question's EBA machine learning model choices, the valid model areas are process behavior and resource behavior. Process reflects what is running or being executed; Resources reflects system or application utilization behavior. Together, these are the two data areas used for EBA machine learning models.
NEW QUESTION # 86
Refer to the exhibit.
If you apply this Group By and Display Fields configuration to a list of network connections, which information will FortiSIEM display?
Answer: B
Explanation:
Grouping by Source IP and Destination IP causes FortiSIEM to aggregate events into unique source-to-destination connection pairs. The matched-events count is displayed for each unique pair, showing how many connections or matching events exist for that grouped relationship.
NEW QUESTION # 87
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