Study NSE6_FSM_AN-7.4 Group | NSE6_FSM_AN-7.4 Preparation

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Fortinet NSE6_FSM_AN-7.4 Exam Syllabus Topics:

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

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                                    Fortinet NSE 6 - FortiSIEM 7.4 Analyst Sample Questions (Q86-Q91):

                                    NEW QUESTION # 86
                                    Which data collection method generates the most comprehensive information for FortiSIEM user entity and behavior analytics (UEBA) models?

                                    Answer: C

                                    Explanation:
                                    The Windows UEBA agent collects detailed user activity and endpoint behavior data specifically designed for FortiSIEM UEBA analytics. It provides richer telemetry for behavioral modeling, anomaly detection, and user activity correlation than standard logs or general-purpose agents.


                                    NEW QUESTION # 87
                                    Refer to the exhibit.


                                    You are attempting to tune an anomaly detection machine learning (ML) job. The chart shows there are no anomalies detected, but you are not satisfied with the fit of the ML model.
                                    Which adjustment must you make to train the model and ensure a better fit?

                                    Answer: B

                                    Explanation:
                                    Increasing the number of windows gives the ML job more historical data windows to use during training. This improves the model's baseline calculation and helps produce a better statistical fit for anomaly detection.


                                    NEW QUESTION # 88
                                    You want FortiSIEM to automatically add three zero trust network access (ZTNA) tags to a device when that device triggers a custom rule. You want FortiSIEM to push these ZTNA tags to multiple FortiClient EMS servers in the organization. How can you accomplish this?

                                    Answer: D

                                    Explanation:
                                    A single playbook can contain multiple connectors, allowing FortiSIEM to push the required ZTNA tags simultaneously to multiple FortiClient EMS servers when the custom rule is triggered.


                                    NEW QUESTION # 89
                                    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 # 90
                                    A critical server is sending traffic that is triggering a high severity outbound intrusion prevention system (IPS) permitted IPS exploit rule. This traffic must be allowed. Which two items must you configure to prevent this sever from triggering the incident? (Choose two.)

                                    Answer: C,E

                                    Explanation:
                                    To stop a known allowed server from generating this incident, you can tune the rule logic by excluding the server IP address in the subpattern filter. You can also create a rule exception for that IP address, which suppresses incident generation for matching traffic from the approved server while leaving the rule active for other sources.


                                    NEW QUESTION # 91
                                    ......

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