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Fortinet FCP_FSM_AN-7.2 Exam Syllabus Topics:

SectionWeightObjectives
Rules and Subpatterns25%- Identify rule components and logic
- Configure subpatterns, aggregation, and correlation
- Create and manage analytics rules
Machine Learning, UEBA, and ZTNA Integration25%- Configure machine learning models and tasks
- Integrate UEBA data into rules and dashboards
- Understand ZTNA integration and visibility
Analytics25%- Apply grouping and aggregation functions
- Use nested queries and advanced lookups
- Perform CMDB and lookup table queries
- Build queries from events and search results
Incidents, Notifications, and Remediation25%- Set up automated remediation actions
- Manage incident lifecycle and prioritization
- Configure alert and notification policies

>> FCP_FSM_AN-7.2 Exam Topics <<

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Fortinet FCP - FortiSIEM 7.2 Analyst Sample Questions (Q38-Q43):

NEW QUESTION # 38
Which statement about thresholds is true?

Answer: A

Explanation:
FortiSIEM evaluates performance metrics against both global thresholds, which apply system-wide, and per-device thresholds, which can be customized for individual devices. This dual approach allows flexibility in monitoring while ensuring consistent baseline alerting.


NEW QUESTION # 39
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: D

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 # 40
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.


NEW QUESTION # 41
Refer to the exhibit.

A FortiSIEM analyst is investigating an issue by examining events related to two destination IP addresses. However, the analyst is not getting any results from the search.
Based on the selected filters shown in the exhibit, why is the search returning no results?

Answer: B

Explanation:
The boolean operator between the two destination IP filters is set to AND, meaning FortiSIEM searches for events where the Destination IP is simultaneously 10.10.10.1 and 192.168.1.1, which is impossible. Changing the operator to OR would return events matching either IP address, producing the expected results.


NEW QUESTION # 42
Refer to the exhibit.

What will happen when a device being analyzed by the machine learning configuration shown in the exhibit has a consistently high memory utilization?

Answer: C

Explanation:
In the configuration shown, FortiSIEM uses Memory Util, Sent Bytes, and Received Bytes as input features to predict CPU Utilization via a regression model. If a device shows consistently high memory utilization, the model will incorporate that into its training data and update itself with a higher average value for memory utilization, influencing future CPU utilization predictions.


NEW QUESTION # 43
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