Exam NSE6_FSM_AN-7.4 Overviews | NSE6_FSM_AN-7.4 Formal Test

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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

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

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NSE6_FSM_AN-7.4 Formal Test | NSE6_FSM_AN-7.4 Exam Simulator Free

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q46-Q51):

NEW QUESTION # 46
You need a model for predicting a target field based on other fields in a dataset and then trigger an anomaly if the value does not match the prediction. Which machine learning algorithm will build this type of model?

Answer: B

Explanation:
A Regression algorithm is used when predicting a continuous or numeric target field based on other features in the dataset. In FortiSIEM, regression-based machine learning models establish expected values, and an anomaly is triggered when the actual observed value significantly deviates from the regression prediction.


NEW QUESTION # 47
Refer to the exhibit. What will happen when a device being analyzed by the machine learning (ML) configuration shown in the exhibit has a consistently high memory use?

Answer: D

Explanation:
The ML regression model uses memory utilization, sent bytes, and received bytes as prediction inputs for CPU utilization. If memory usage remains consistently high, FortiSIEM adapts the learned baseline and updates the model with a higher average memory utilization value over time.


NEW QUESTION # 48
Refer to the exhibit. Why is this search not producing any results?

Answer: C

Explanation:
The query contains a nested query attribute type mismatch because the User attribute is being compared against a Device IP group value. The attribute type and referenced group type must match for the search to return results.


NEW QUESTION # 49
Refer to the exhibit. If you group the events by Reporting IP, Event Type, and User attributes, how many results will FortiSIEM display?

Answer: B

Explanation:
When grouped by Reporting IP, Event Type, and User, FortiSIEM consolidates rows sharing the same values for these attributes.
Reporting IP: all are 10.1.1.1
Event Type: all are Logon
Users: Mike, Bob, and Alice
Thus, FortiSIEM will display three results, one for each user.


NEW QUESTION # 50
An analyst wants to create a rule from a new analytic search they just performed. Which method is the most efficient way for you to create the rule?

Answer: D

Explanation:
Using the Create Rule option directly from the Actions menu is the most efficient method because it automatically converts the existing analytic search into a rule structure without requiring manual reconfiguration.


NEW QUESTION # 51
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