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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

SectionObjectives
Topic 1: 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
Topic 2: Rules and Incident Management- Incidents and Notifications
  • 1. Configure notification policies
  • 2. Manage and tune incidents
  • 3. Configure remediation options
- Rules and Alerts
  • 1. Identify various rule components
  • 2. Configure FortiSIEM analytics rules
  • 3. Utilize rule subpatterns, aggregation, group by
Topic 3: 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
Topic 4: 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)

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Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q18-Q23):

NEW QUESTION # 18
When using user and entity behavior analytics (UEBA) on FortiSIEM, what must you use to dynamically supply a list of IP addresses to a FortiGate device for blocking purposes?

Answer: D


NEW QUESTION # 19
Refer to the exhibit.

You are investigating an issue with two destination IP addresses, but you are not getting any results from the search.
Based on the filters shown in the exhibit, why is this search returning no results?

Answer: C

Explanation:
The search is using an AND condition between two different values for the same Destination IP attribute. A single event cannot have both destination IP addresses at the same time, so the filter returns no results. The condition should use OR to search for events matching either destination IP address.


NEW QUESTION # 20
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?

Answer: A

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 # 21
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: A

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 # 22
When configuring machine learning (ML), in which step can you modify how the model fits the training data set?

Answer: D

Explanation:
The Statistics step is where you tune statistical model parameters that affect how closely the machine learning model fits the training data set, such as deviation-related settings used for anomaly detection.


NEW QUESTION # 23
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