Intrusion detection data
Intrusion detection data refers to the information collected, analyzed, and generated by an intrusion detection system (IDS) to monitor network and system activity for potential security breaches, policy violations, or malicious activity. This data helps identify unauthorized access, cyber attacks, or anomalies that could compromise network security or application performance.
Intrusion detection data can include logs, alerts, traffic patterns, threat signatures, and behavior analysis results. It is critical for organizations to monitor, investigate, and respond to potential intrusions effectively. Intrusion detection data is often integrated with SIEM tools like Splunk Enterprise Security for centralized analysis and correlation with other security data. Intrusion detection systems must handle sensitive data securely, as they monitor both internal and external network activity.
Examples of intrusion detection data include the following:
- Traffic analysis logs: Data about network traffic patterns analyzed by the IDS
- Signature-based detection data Data generated when traffic matches predefined threat patterns or signatures
- Anomaly detection data: Data about deviations from normal traffic or behavior patterns
- Host-based intrusion detection data: Data collected from specific hosts or endpoints
- Network-based intrusion detection data: Data collected from network traffic passing through routers, switches, or firewalls
- Alerts and notifications: Alerts generated by the IDS based on detected threats or anomalies
- Threat intelligence data: Data enriched with external threat intelligence feeds for context
- Attack pattern data: Data about specific attack methodologies or tactics
- Event correlation data: Data that combines multiple related events into a single detection
- Compliance and audit data: Data collected for regulatory compliance or auditing purposes
- Forensic analysis data: Data used for post-incident investigations
- False positive/false negative data: Information about incorrectly flagged or missed threats
- Behavioral analysis data: Data about user or system behavior used to detect anomalies
- System performance data: Metrics about the performance and health of the IDS
The Splunk Common Information Model (CIM) add-on contains an Intrusion Detection data model with fields that describe attack detection events gathered by network monitoring devices and apps. The network traffic in the Intrusion Detection data model is allowed or denied based on complex traffic patterns. Traffic is continuously monitored by the intrusion detection systems and might be denied passage in the middle of an existing connection based on known signatures or bad traffic patterns.