Microsoft Security Operations Analyst Associate SC-200 Practice Question
Your organization ingests alerts from Microsoft Defender for Endpoint and Azure Active Directory Identity Protection into Microsoft Sentinel. You must automatically correlate related alerts from these sources into a single incident that represents a multistage attack. When creating the analytics rule, which rule type should you choose, and what prerequisite must be satisfied for the rule to work?
Machine-learning behavior analytics rule; turn on User and Entity Behavior Analytics (UEBA) in the Settings page.
Fusion rule template; ensure that at least one supported Microsoft security data connector (such as Microsoft Defender for Endpoint or Azure AD Identity Protection) is enabled in the workspace.
Scheduled rule; configure alert grouping to Correlate alerts across subscriptions before saving the rule.
Microsoft incident creation rule; verify that the Log Analytics workspace is hosted in an Azure region that supports the Microsoft Security Graph.
The Fusion analytics rule type uses built-in machine-learning models to correlate alerts from multiple Microsoft security products into a single high-fidelity incident that represents a multistage attack. For Fusion to function, at least one of its supported Microsoft security data connectors (for example, Microsoft Defender for Endpoint or Azure AD Identity Protection) must already be enabled and actively streaming alerts into the workspace. Other rule types such as scheduled rules, Microsoft incident creation rules, or machine-learning behavior analytics rules either do not perform cross-product correlation automatically or require different prerequisites (for example, UEBA enablement), so they would not meet the requirement in this scenario.
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Microsoft Security Operations Analyst Associate SC-200
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