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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Event Collection and Normalization	20%	- Normalizing, parsing, and standardizing event data - Collecting logs and data from multiple sources
Topic 2: Event Correlation and Rule Management	20%	- Managing alerts, tuning rules, reducing false positives - Creating and configuring correlation rules
Topic 3: Analytics	30%	- Applying group by and data aggregation - Building queries from search results and events - Performing CMDB and lookup table queries
Topic 4: Incident Detection, Investigation and Response	15%	- Using dashboards and tools for incident investigation - Applying incident response workflows and escalation
Topic 5: Monitoring, Reporting and Integration	15%	- Generating compliance and operational reports - Integrating with security tools and ZTNA - Configuring dashboards and real-time monitoring

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q92-Q97):

NEW QUESTION # 92
Which two attributes can you not select together in the Group By and Display Fields? (Choose two.)

A. Raw Event Log
B. Source IP
C. Destination IP
D. Event Reporting Time
E. Reporting IP

Answer: A,C

NEW QUESTION # 93
Refer to the exhibit. Which value will the FortiSIEM parser use to populate the Application Name field?

A. Network.Service: SSL
B. Network.Service
C. SSL
D. Network Service

Answer: C

Explanation:
The raw FortiGate event includes app="SSL", and the parser uses this value to populate the Application Name field.

NEW QUESTION # 94
You want to build a query that includes only events that contain a username.
What is a valid analytics query that will perform this type of search?

A. User IS VALID
B. User IS NOT NULL
C. User STARTS_WITH *
D. User CONTAIN *

Answer: B

Explanation:
A query using IS NOT NULL returns only events where the User attribute has a value. This is the valid way to filter analytics results to events that contain a username.

NEW QUESTION # 95
Refer to the exhibit.

An incorrect configuration is shown.
Which setting must you change to successfully apply this configuration to FortiSIEM?

A. Set the algorithm to Anomaly Detection.
B. Set the Train factor to 70% or greater.
C. Set the Run Mode to ML.
D. Select the same values in the Fields to use for Prediction and Field to Predict sections.

Answer: B

Explanation:
For a regression machine learning job, the train factor must allocate enough data for model training. Setting it to 70% or greater provides sufficient training data so FortiSIEM can successfully apply and train the model configuration.

NEW QUESTION # 96
How does FortiSIEM update the incident details if the same rule triggers repeatedly?

A. FortiSIEM changes the incident status to Repeated, and updates the Last Seen timestamp.
B. FortiSIEM generates a new incident based on the Rule Frequency value, and updates the First Seen and Last Seen timestamps.
C. FortiSIEM generates a new incident each time the rule triggers and updates all the First Seen and Last Seen timestamps.
D. FortiSIEM updates the Incident Count value and Last Seen timestamp.

Answer: D

Explanation:
When the same rule triggers repeatedly for an existing incident, FortiSIEM updates the Incident Count and refreshes the Last Seen timestamp while maintaining the original incident record.

NEW QUESTION # 97
......

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