Skip to main content
Network Monitoring in SOC for Cybersecurity

Network Monitoring in SOC for Cybersecurity

$250.00
Who trusts this:
Trusted by professionals in 160+ countries
Your guarantee:
30-day money-back guarantee — no questions asked
How you learn:
Self-paced • Lifetime updates
Toolkit Included:
Includes a practical, ready-to-use toolkit containing implementation templates, worksheets, checklists, and decision-support materials used to accelerate real-world application and reduce setup time.
When you get access:
Course access is prepared after purchase and delivered via email
Adding to cart… The item has been added

What does the Network Monitoring in SOC for Cybersecurity course cover?

Network Monitoring in SOC for Cybersecurity is covered here in 8 modules: Architecting a Scalable Monitoring Infrastructure, Deploying and Tuning Detection Sensors, Centralized Log Aggregation and Normalization and 5 more. The outline lists 48 specific topics, opening with select network tap vs. SPAN port deployment based on traffic volume, encryption handling, and failure domain isolation requirements.

How do you approach Network Monitoring in SOC for Cybersecurity step by step?

The work is sequenced in 8 stages. It starts with Architecting a Scalable Monitoring Infrastructure, moves through Deploying and Tuning Detection Sensors and Centralized Log Aggregation and Normalization, and ends at Performance Optimization and Capacity Planning. Each stage carries its own topic list, so the sequence is followed rather than summarised.

What is in Module 1 of the Network Monitoring in SOC for Cybersecurity course?

Module 1 is Architecting a Scalable Monitoring Infrastructure. It works through select network tap vs. SPAN port deployment based on traffic volume, encryption handling, and failure domain isolation requirements., design redundant packet capture paths to prevent blind spots during switch or sensor failures in critical network segments., allocate sufficient storage and retention policies for full packet capture (PCAP) based on compliance mandates.

How is the Network Monitoring in SOC for Cybersecurity course delivered?

The Network Monitoring in SOC for Cybersecurity course is fully self-paced with immediate online access after enrolment. Access does not expire and future updates are included at no cost. It can be taken on any device, and a certificate of completion is issued by The Art of Service when you finish.

How much does the Network Monitoring in SOC for Cybersecurity course cost?

The Network Monitoring in SOC for Cybersecurity course is $250 as a one time payment. There is no subscription, no per seat licence and no hidden fee. Enrolment carries a 30 day satisfied or refunded guarantee, so it can be assessed in full before you commit.

Closely related courses: Cybersecurity Monitoring in SOC for Cybersecurity, Cloud Security Monitoring in SOC for Cybersecurity, File Integrity Monitoring in SOC for Cybersecurity, Cybersecurity Monitoring and SOC 2 Type 2 Kit.

More answers: what you get with every course, refund policy, all help answers.

This curriculum spans the technical and operational rigor of a multi-phase SOC modernization initiative, covering the design, deployment, and governance of network monitoring systems at the scale of an enterprise-wide security operations program.

Module 1: Architecting a Scalable Monitoring Infrastructure

  • Select network tap vs. SPAN port deployment based on traffic volume, encryption handling, and failure domain isolation requirements.
  • Design redundant packet capture paths to prevent blind spots during switch or sensor failures in critical network segments.
  • Allocate sufficient storage and retention policies for full packet capture (PCAP) based on compliance mandates and forensic needs.
  • Implement time synchronization across all monitoring devices using NTP with authenticated sources to ensure log correlation accuracy.
  • Integrate monitoring sensors behind NAT or in cloud VPCs with consistent metadata tagging for source attribution.
  • Size monitoring appliances based on peak bandwidth utilization and protocol decomposition overhead for encrypted traffic.

Module 2: Deploying and Tuning Detection Sensors

  • Configure IDS/IPS rulesets to suppress known benign traffic patterns without reducing sensitivity to novel attack vectors.
  • Adjust Snort or Suricata rule thresholds to balance false positives with detection coverage for lateral movement.
  • Deploy TLS decryption at strategic chokepoints, weighing privacy compliance against visibility needs.
  • Validate sensor placement at east-west and north-south boundaries to capture internal pivoting and external exfiltration.
  • Use passive fingerprinting to detect rogue or unauthorized devices in segmented environments.
  • Implement protocol anomaly detection for DNS, HTTP, and SMB to identify beaconing and tunneling behavior.

Module 3: Centralized Log Aggregation and Normalization

  • Define parsing rules in SIEM to normalize fields from heterogeneous sources like firewalls, proxies, and EDR.
  • Optimize log forwarding intervals and batching to reduce network overhead without introducing detection delays.
  • Apply retention tiering: hot storage for active investigations, cold storage for compliance audits.
  • Enforce secure transport (TLS with mutual authentication) for log transmission from endpoints to central collectors.
  • Map custom log fields to standard taxonomies (e.g., MITRE ATT&CK) for consistent correlation rule development.
  • Monitor log source health and detect gaps using heartbeat alerts from forwarders and collectors.

Module 4: Real-Time Correlation and Alerting Logic

  • Develop correlation rules that chain low-severity events (e.g., failed logins followed by successful access from new geolocations).
  • Supress alerts for scheduled administrative activities using time-based allow lists tied to change management records.
  • Implement threshold-based detection for brute force attacks using dynamic baselines adjusted for user roles.
  • Use asset criticality tags to prioritize alerts from high-value systems in correlation logic.
  • Integrate threat intelligence feeds to enrich alerts with context, while filtering stale or low-confidence indicators.
  • Validate alert logic using historical data to measure detection rate and false positive impact before production rollout.

Module 5: Network Traffic Analysis and Behavioral Baselines

  • Establish baseline communication patterns for service accounts and flag deviations indicating compromise.
  • Apply machine learning models to detect data exfiltration via volume and timing anomalies in outbound traffic.
  • Monitor DNS query frequency and entropy to identify domain generation algorithm (DGA) usage.
  • Use NetFlow/IPFIX to reconstruct communication graphs and identify unexpected peer-to-peer host relationships.
  • Track protocol deviations, such as SSH over non-standard ports, to detect covert channels.
  • Compare encrypted traffic metadata (e.g., packet size, timing) against known malware C2 patterns.

Module 6: Integration with Incident Response Workflows

  • Automate host isolation via API integration between SIEM and endpoint protection platforms upon confirmed compromise.
  • Predefine playbook templates for common scenarios (e.g., ransomware, credential theft) with manual approval gates.
  • Ensure monitoring tools export data in standardized formats (e.g., STIX/TAXII) for external threat sharing.
  • Preserve raw packet captures and session logs during incident containment for forensic validation.
  • Coordinate with network teams to implement temporary traffic mirroring for deep-dive analysis during active incidents.
  • Document sensor coverage gaps during post-incident reviews and update monitoring scope accordingly.

Module 7: Governance, Compliance, and Audit Readiness

  • Map monitoring controls to regulatory frameworks (e.g., NIST, ISO 27001, GDPR) for audit evidence preparation.
  • Restrict access to raw network data based on role-based permissions and data sensitivity classification.
  • Conduct quarterly access reviews for SOC analysts with privileges to view full packet captures.
  • Implement immutable logging for monitoring system configuration changes to support chain-of-custody requirements.
  • Document data retention policies aligned with legal hold procedures and jurisdiction-specific regulations.
  • Perform annual third-party assessments of monitoring infrastructure for configuration drift and blind spots.

Module 8: Performance Optimization and Capacity Planning

  • Monitor sensor CPU and memory utilization to identify saturation during traffic spikes or DDoS events.
  • Adjust sampling rates on high-throughput links when full capture is infeasible, documenting coverage trade-offs.
  • Forecast storage growth based on network expansion and new data sources like cloud workloads.
  • Optimize SIEM indexing strategies by excluding non-essential fields to reduce storage and query latency.
  • Validate failover procedures for log collectors during maintenance or outages to prevent data loss.
  • Conduct load testing on correlation engine before deploying complex, resource-intensive rulesets.
!