Anomaly-based IDS
Anomaly-based Intrusion Detection System (IDS) is a type of security system that uses machine learning algorithms to detect abnormal behavior in network traffic, system calls, or user activity. Anomaly-based IDS works by creating a baseline of normal behavior and then monitoring for deviations from that baseline. When an anomaly is detected, the system generates an alert or takes other actions to mitigate the threat. Anomaly-based IDS is particularly effective at detecting previously unknown attacks or zero-day exploits, as it does not rely on known attack signatures. However, it can also generate false positives if the baseline is not properly calibrated or if there are legitimate changes in behavior that are not malicious.
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