How does Azure Security Center use machine learning?
Date:2023-01-09
Azure Security Center uses machine learning to detect threats and anomalous behavior that could indicate a security breach. It can analyze patterns of network traffic and identify malicious activity, such as suspicious logins or traffic flows. It also monitors user accounts and data access to identify anomalies that could point to a security breach. Machine learning algorithms are used to detect and analyze uncommon and abnormal activity and then automatically alert security teams of potential threats. Additionally, parameter mining is used to detect resource misconfigurations that could lead to attack opportunities or system misconfigurations. Overall, machine learning can be used to provide enhanced security intelligence and improve threat detection and mitigation for Azure environments.
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