Rule-based detection methods rely on predefined rules and patterns that are known beforehand. These rules are created based on prior knowledge of what constitutes normal and abnormal behavior.

Statistical detection, on the other hand, involves analyzing data to identify anomalies. It is based on assumptions about what normal behavior looks like and uses statistical methods to detect deviations from this norm.

Rule-based systems are typically straightforward but may miss novel attacks that do not match existing rules.

Statistical methods can detect previously unknown threats by recognizing patterns that deviate from established baselines but may produce more false positives.

References

Intrusion Detection Systems (IDS) Concepts

Comparative Studies on Rule-based and Statistical Anomaly Detection

Understanding Anomaly Detection in Network Security