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| Section | Objectives |
|---|---|
| Analytics and Search | - Query and Event Analysis
|
| FortiEDR and Security Policy Integration | - FortiEDR Security Configuration
|
| Advanced Analytics and Integrations | - ML, UEBA, and ZTNA
|
| Rules and Incident Management | - Incidents and Notifications
|
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NEW QUESTION # 65
Refer to the exhibit.
If you apply this Group By and Display Fields configuration to a list of network connections, which information will FortiSIEM display?
Answer: C
Explanation:
Grouping by Source IP and Destination IP causes FortiSIEM to aggregate events into unique source-to-destination connection pairs. The matched-events count is displayed for each unique pair, showing how many connections or matching events exist for that grouped relationship.
NEW QUESTION # 66
When configuring machine learning (ML), in which step can you modify how the model fits the training data set?
Answer: B
Explanation:
The correct answer is B. Train. In FortiSIEM machine learning, the Train step is where the model is built from the prepared dataset and where model-fitting behavior can be adjusted. The FortiSIEM 7.4 User Guide explains that after preparing data, the analyst goes to Analytics > Machine Learning > Train, selects the machine learning task, chooses the algorithm, selects the prediction/target fields when required, and chooses the Train factor, which determines how much data is used for training versus testing. The guide states that the Train factor should be greater than 70%, meaning 70% of the data is used for training and 30% for testing. It also explains that model quality metrics show how accurately the algorithm predicts the field. For regression, lower MAE means a better fit, and R2 shows how well predictions approximate real data points. Most importantly, the guide states: "If you want to change the algorithm parameters and re-train, then click Tune & Train, change the parameters and click Save
& Train." This confirms that modifying how the model fits the training dataset is done in the Train step, not Prepare Data, Statistics, or Design.
NEW QUESTION # 67
Refer to the exhibit.
Which two conditions will match this rule and subpatterns? (Choose two.)
Answer: A,C
Explanation:
The user initiates an RDP session (Subpattern 1) and then fails to log in multiple times (Subpattern 2 with COUNT(Matched Events) > = 3) - both from the same Source IP and User within 300 seconds.
The brute force attempts typically involve a successful RDP connection followed by multiple failed logins, satisfying the sequence and grouping conditions in the rule.
The correct answers are A and B because the rule uses multiple subpatterns and requires them to occur in a defined relationship within the configured time window. The FortiSIEM Study Guide states that rule conditions specify the event attributes and thresholds that trigger the rule and create an incident. It also explains that the time window is the period "within which the subpattern(s) must match for the rule condition to be satisfied," and that when there is more than one subpattern, FortiSIEM requires logic between the subpatterns plus subpattern relationship constraints. In the exhibit, the first subpattern detects an RDP connection and the second detects failed logons. The rule condition uses a sequence relationship, so the failed logon activity must follow the RDP connection and match the relationship constraints, such as same user and source IP. A user using RDP over SSL VPN who fails repeatedly satisfies this logic. A brute-force attack against an RDP server also satisfies the repeated failed-logon requirement after an RDP connection. Failing only twice does not meet the aggregate threshold, and connecting to the wrong IP is not the failed-logon sequence being detected.
NEW QUESTION # 68
Refer to the exhibit.
An analyst wants to perform a KMeans machine learning (ML) job on this data.
How many N clusters would be a good fit for the data?
Answer: D
Explanation:
The scatter plot shows two visually distinct groupings of data points, making two clusters an appropriate fit for a KMeans ML job.
NEW QUESTION # 69
What must match when referencing an inner query from an outer query?
Answer: C
Explanation:
When creating an inner query in FortiSIEM, the referenced attribute in the outer and inner queries must share the same data type (for example, IP address, string, or integer). This ensures the system can properly correlate and filter results between the two queries during execution.
NEW QUESTION # 70
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