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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

Section	Objectives
Machine Learning, UEBA, and ZTNA	- Advanced analytics integration 1. Describe ZTNA integration in FortiSIEM operations 2. Integrate UEBA data into rules and dashboards 3. Configure ML configuration tasks
Rules and Subpatterns	- Analytics rules configuration 1. Configure FortiSIEM analytics rules 2. Use rule subpatterns, aggregation, and group by 3. Identify rule components
FortiEDR Security Settings and Policies	- Security configuration 1. Configure playbooks 2. Configure security policies 3. Explain Fortinet Cloud Service (FCS) 4. Configure communication control policy
Analytics	- Query and event analysis 1. Perform nested query lookups 2. Apply group by and data aggregation on search results 3. Perform CMDB and lookup table queries 4. Build queries from search results and events
Incidents, Notifications, and Remediation	- Incident management 1. Configure remediation options 2. Manage and tune incidents 3. Configure notification policies

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q65-Q70):

NEW QUESTION # 65
Refer to the exhibit.

The configuration shown in the exhibit is incorrect.
What must you change to allow this configuration to be successfully applied to FortiSIEM?

A. Only one AVG type field must be selected under Fields to use for Prediction.
B. The Train factor must be 70% or greater.
C. Run Mode must be set to ML.
D. The selection in Fields to use for Prediction and Field to Predict must match.

Answer: B

Explanation:
The correct answer is A . In FortiSIEM machine learning training, the Train factor controls how much of the prepared dataset is used for training and how much is reserved for testing. The FortiSIEM 7.4 User Guide states in the regression training procedure that the analyst must choose the Train factor and that it "should be greater than 70%." It also explains the meaning of the value: 70% of the data is used for training and 30% is used for testing. This directly supports option A. Option B is incorrect because the supported running modes include Local, Local Auto, and AWS; "ML" is not the required run mode. Option C is incorrect because regression can use multiple fields for prediction; the guide instructs the user to choose the fields to use for prediction and the field to predict. Option D is incorrect because prediction input fields and target field should not be the same. Regression builds a model to predict a target field based on other fields, so the configuration must use a valid Train factor rather than matching predictor and target fields.

NEW QUESTION # 66
You need a model that predicts a target field based on other fields in a dataset and then triggers an anomaly if the value does not match the prediction. Which machine learning (ML) algorithm will you use to build this type of model?

A. Classification
B. Forecasting
C. Regression
D. Anomaly detection

Answer: C

Explanation:
Regression models predict the value of a target field using other fields as predictors. FortiSIEM can then generate anomalies when the observed value significantly deviates from the predicted value.

NEW QUESTION # 67
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?

A. The Fortinet Security Fabric
B. FortiSIEM lookup tables
C. Secure Copy Protocol (SCP)
D. FortiSIEM watchlists

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 # 68
Refer to the exhibit. What will FortiSIEM display if you apply the Group By and Display Fields configuration to a list of allowed firewall connections?

A. A list of connections ordered by destination IP address hit count
B. A list of connections ordered by the number of unique connections started by each source IP address
C. A list of connections between unique source and destination IP addresses
D. A running count of connections, regardless of source or destination

Answer: C

Explanation:
With Source IP and Destination IP as grouping attributes, and COUNT(Matched Events) included, FortiSIEM will display a list of unique source-destination IP pairs along with the number of allowed connections between each pair. This configuration summarizes connection activity by unique communication paths.

NEW QUESTION # 69
Refer to the exhibit.

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

A. The Event Receive Time attribute is not available for logs.
B. No RAW Event Log attribute information is available.
C. Unique values cannot be grouped
D. The attribute COUNT(Matched Events) is an invalid expression.

Answer: C

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 # 70
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