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Fortinet FCP_FSM_AN-7.2 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Machine learning, UEBA, and ZTNA: This section of the exam measures the skills of Advanced Security Architects and covers the integration of modern security technologies. It involves performing configuration tasks for machine learning models, incorporating UEBA (User and Entity Behavior Analytics) data into rules and dashboards for enhanced threat detection, and understanding how to integrate ZTNA (Zero Trust Network Access) principles into security operations.
Topic 2
  • Analytics: This section of the exam measures the skills of Security Analysts and covers the foundational techniques for building and refining queries. It focuses on creating searches from events, applying grouping and aggregation methods, and performing various lookup operations, including CMDB and nested queries to effectively analyze and correlate data.
Topic 3
  • Incidents, notifications, and remediation: This section of the exam measures the skills of Incident Responders and encompasses the entire incident management lifecycle. This includes the skills required to manage and prioritize security incidents, configure policies for alert notifications, and set up automated remediation actions to contain and resolve threats.
Topic 4
  • Rules and subpatterns: This section of the exam measures the skills of SOC Engineers and focuses on the construction and implementation of analytics rules. It involves identifying the different components that make up a rule, utilizing advanced features like subpatterns and aggregation, and practically configuring these rules within the FortiSIEM platform to detect security events.

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

NEW QUESTION # 38
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 # 39
Refer to the exhibit.

How was this incident cleared?

Answer: B

Explanation:
The Incident Status shows "Auto Cleared", and the Cleared Reason states: "Rule has not been triggered for 20 minutes." This indicates that the incident was automatically cleared by the rule logic after a defined period of inactivity.


NEW QUESTION # 40
Refer to the exhibit.

Which value would you expect the FortiSIEM parser to use to populate the Application Name field?

Answer: D

Explanation:
The Application Name field in FortiSIEM is typically populated using the value of the app field in the raw log. In this event, app="SSL", so "SSL" is the expected application name parsed by FortiSIEM.


NEW QUESTION # 41
How can you query the configuration management database (CMDB) in an analytics search?

Answer: C

Explanation:
In an analytics search, you can query the CMDB by clicking Value > Select from CMDB, which allows you to choose values directly from CMDB entries for the selected attribute, enabling precise filtering based on asset data.


NEW QUESTION # 42
From which two sources can you import data to train FortiSIEM machine learning? (Choose two.)

Answer: A,B


NEW QUESTION # 43
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