Network Traffic Analysis and Monitoring Questions

Covers the techniques and practices for observing, collecting, and analyzing network traffic to detect suspicious behavior and security anomalies. Candidates should understand packet capture and deep packet inspection, network flow data collection and interpretation such as NetFlow and sFlow, domain name system monitoring, and application level behavior analysis. Expect to explain how to identify indicators of compromise in network data including command and control communication, data exfiltration patterns, lateral movement, and protocol misuse or anomalies. The topic includes knowledge of common tools and platforms for network analysis and monitoring such as Wireshark, Zeek, Suricata, tcpdump, and network flow collectors, as well as how to integrate network telemetry with security information and event management platforms and threat intelligence feeds. Candidates should be able to compare approaches and select the right tooling for packet level forensics versus flow based detection. Interviewers will probe detection techniques including signature based detection, rule and heuristic based methods, statistical anomaly detection, and machine learning approaches; as well as practical concerns such as establishing baselines, threshold tuning, reducing false positives, alert triage workflows, and threat hunting using network data. Operational aspects that may be assessed include sensor placement and capture methods such as network taps and span ports, encrypted traffic challenges and when transport layer security inspection is needed, metadata enrichment, retention and evidence preservation for investigations, and coordination with incident response and forensic processes. Candidates should be able to describe investigative steps, typical investigation artifacts, and how network monitoring contributes to detection and response.