What are the features of anomaly detection in network traffic (Zeek, Netflow)?

Anomaly detection in network traffic using Zeek and Netflow has several features:

• Context-aware analysis: Zeek collects detailed event logs at the protocol level (HTTP, DNS, SSL, etc.), allowing the detection of anomalies not only based on traffic volume but also on protocol and session behavior.

• Multi-level data: Netflow provides aggregated data about traffic flows (IP addresses, ports, volumes, durations), which is well-suited for identifying anomalies in communication patterns (e.g., DDoS, port scanning).

• Handling large volumes: Both tools generate large amounts of data, so anomaly detection algorithms need to be efficient and scalable.

• Types of anomalies: Both statistical anomalies (sudden traffic spikes) and behavioral anomalies (unusual request sequences, new protocols) can be detected.

• Use of heuristics and ML: Rules (e.g., threshold values) are often combined with machine learning to improve accuracy.

Example: Using Zeek, you can analyze DNS query logs and identify anomalous domains that are frequently queried within a short period, which may indicate a botnet.