CyberOps Associate 200-201 Cisco Study Notes

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

Cisco Application Visibility and Control (AVC) provides features like metrics collection and exporting (D) for visibility on TCP bandwidth usage, response time, and latency. Application recognition (E) combined with deep packet inspection helps in identifying unknown software by its network traffic flow. References := Cisco CyberOps Associate - Module 2: Security Concepts

 To investigate the callouts made post infection, it’s essential to know where the callouts were made to (domain names) and from which host IP addresses they originated. This information can help trace back the source and destination, aiding in understanding the nature of the callouts. References: