Fortinet - NSE6_FSM_AN-7.4 - Fortinet NSE 6 - FortiSIEM 7.4 Analyst–Efficient Test Dumps Free

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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

SectionObjectives
Advanced Analytics and Integrations- ML, UEBA, and ZTNA
  • 1. Configure machine learning (ML) settings
  • 2. Integrate UEBA data into rules and dashboards
  • 3. Describe ZTNA integration in FortiSIEM operations
Rules and Incident Management- Rules and Alerts
  • 1. Identify various rule components
  • 2. Configure FortiSIEM analytics rules
  • 3. Utilize rule subpatterns, aggregation, group by
- Incidents and Notifications
  • 1. Configure notification policies
  • 2. Configure remediation options
  • 3. Manage and tune incidents
FortiEDR and Security Policy Integration- FortiEDR Security Configuration
  • 1. Configure playbooks
  • 2. Configure communication control policy
  • 3. Explain Fortinet Cloud Service (FCS)
  • 4. Configure security policies
Analytics and Search- Query and Event Analysis
  • 1. Perform nested query lookups
  • 2. Perform CMDB and lookup table queries
  • 3. Apply group by and data aggregation
  • 4. Build queries from search results and events

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q27-Q32):

NEW QUESTION # 27
Which two data areas can you use for user and entity behavior analytics (EBA) machine learning models?
(Choose two.)

Answer: A,C

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 # 28
When using user and entity behavior analytics (UEBA) on FortiSIEM, what can you use to dynamically supply a list of suspicious IP addresses to FortiGate for blocking?

Answer: D

Explanation:
FortiSIEM watchlists can dynamically maintain suspicious entities, such as IP addresses identified through UEBA rules or analytics. These watchlists can then be used to provide FortiGate with an updated list of IP addresses for automated blocking.


NEW QUESTION # 29
Refer to the exhibit. Which event type attribute value will the FortiSIEM parser save for this event?

Answer: B

Explanation:
FortiSIEM parsers map raw event attributes to normalized event type attributes. In this event, the parser identifies the sysUpTime value and stores it under the normalized FortiSIEM attribute name PH_DEV_MON_SYS_UPTIME.


NEW QUESTION # 30
Refer to the exhibit.

As shown in the exhibit, why are some of the fields highlighted in red?

Answer: A

Explanation:
The fields are highlighted in red because unique values such as Event Receive Time and Raw Event Log cannot be used in group-by operations. Grouping requires aggregatable or consistent values across events, while these fields are unique to each event, making them incompatible for grouping.
The correct answer is A because the highlighted fields are not valid for that grouped/aggregated display configuration. The FortiSIEM 7.4 User Guide notes that some event attributes, functions, and queries are not supported in specific analytics result-filter and display contexts. It lists date fields, including examples such as Event Receive Time , and also lists Raw Event Log and Binary Raw Event Log among unsupported fields for that context. The reason is practical: grouping requires stable values that can combine multiple events into meaningful grouped rows. Attributes such as Event Receive Time and Raw Event Log are highly specific to individual events. If every event has its own receive timestamp or unique raw log content, grouping by those fields defeats aggregation and can create one row per event rather than meaningful grouped output. COUNT (Matched Events) itself is a valid aggregate expression when used correctly. Event Receive Time is available in logs, but it is not appropriate as a grouped field in the configuration shown. Therefore, the red highlighting indicates invalid grouped fields caused by unique/non-groupable values.


NEW QUESTION # 31
Refer to the exhibit. What is the Group: VPN Gateway value referring to?

Answer: B

Explanation:
The value Group: VPN Gateway refers to a CMDB device group in FortiSIEM. This group represents a collection of devices categorized as VPN Gateways in the Configuration Management Database. By filtering with this group, the query retrieves events where the Source IP matches any device included in the CMDB group "VPN Gateway."


NEW QUESTION # 32
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