What are three characteristics of SIEM?

Data Collection: SIEM systems collect data from a variety of sources, including network devices, servers, applications, and endpoints. This data is typically in the form of logs or event records, and is forwarded to the SIEM for analysis. Log Management: SIEM systems store and manage large volumes of log data, which can be used for analysis and reporting. This data is typically stored in a centralized repository and can be searched, filtered, and analyzed using various tools and techniques. Event Correlation: SIEM systems use event correlation techniques to identify relationships between different events and to detect potential security threats. This involves analyzing data from multiple sources and looking for patterns and anomalies that may indicate a security incident. Threat Detection: SIEM systems use a variety of techniques to detect potential security threats, including signature-based detection, anomaly detection, and behavior analysis. These techniques are designed to identify known threats, as well as unknown or advanced threats that may be missed by traditional security measures. Alerting and Reporting: SIEM systems generate alerts and reports when potential security threats are detected. These alerts can be sent to security teams or other stakeholders, and can be customized to reflect the severity of the threat and the organization's response procedures. Incident Response: SIEM systems provide tools and workflows to help security teams investigate and respond to security incidents. This may include automated response actions, such as blocking network traffic or isolating compromised endpoints, as well as manual investigation and remediation procedures.