AI monitoring Monitoring and Detection: Lab Series
RCCE students will learn AI threat modeling, prompt injection defenses, model security, AI data protection, and responsible AI deployment. RCCE students will learn to secure AI systems throughout their lifecycle, protect training data and model integrity, detect adversarial attacks against machine learning systems, and establish governance frameworks for safe AI operations. This monitoring course teaches comprehensive detection and observability strategies for proactive security operations. At an expert level, RCCE students will learn to instrument systems for security telemetry, build detection pipelines, configure alerting, and maintain monitoring coverage as environments evolve. Students gain the visibility and detection capabilities needed to catch threats early.
- Security Engineers building defensive controls
- Security Analysts and Blue Team members
- Systems Administrators with security responsibilities
- GRC and Risk Professionals supporting controls
- Professionals implementing AI monitoring Monitoring and Detection: Lab Series
- Monitor and audit privilege usage; detect escalation attempts
- Build detections and response workflows for privilege escalation
- Execute hands-on tasks for business continuity • disaster recovery • ransomware preparedness
- Execute hands-on tasks for recovery & resilience
- Monitor and audit privilege usage; detect escalation attempts, including Integrated Outcome.
- Execute hands-on tasks for business continuity planning fundamentals
- Execute hands-on tasks for governance framework — covering Business impact analysis (BIA), Executive sponsorship required.
- Execute hands-on tasks for business impact analysis deep dive
- Execute hands-on tasks for quantitative analysis — covering Revenue loss per hour of downtime.
- Execute hands-on tasks for qualitative analysis — covering Reputation and brand damage.
- Execute hands-on tasks for bia deliverables — covering Critical process inventory with priority tiers.
| Module 01 | Recovery Testing Monitoring |
| Module 02 | and Detection: Lab Series |
| Module 03 | Business Continuity • Disaster Recovery • Ransomware Preparedness |
| Module 04 | High Availability • Detection Pipelines • Security Observability |
| Module 05 | Recovery & Resilience |
| Module 06 | Monitoring & Detection |
| Module 07 | Business Continuity Planning Fundamentals |
| Module 08 | Governance Framework |
| Module 09 | Business Impact Analysis Deep Dive |
| Module 10 | Quantitative Analysis |
| Module 11 | Qualitative Analysis |
| Module 12 | BIA Deliverables |
| Module 13 | Recovery Point |
| Module 14 | Recovery Time |
All hands-on labs run on Rocheston Rose X OS. Students practice ai monitoring monitoring and detection: lab series by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.
- Lab 1: Monitor and audit privilege usage; detect escalation attempts
- Lab 2: Build detections and response workflows for privilege escalation
- Lab 3: Execute hands-on tasks for business continuity • disaster recovery • ransomware preparedness
- Lab 4: Build detections and response workflows for privilege escalation
- Lab 5: Execute hands-on tasks for recovery & resilience
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for AI monitoring Monitoring and Detection: Lab Series, verifiable through the Rocheston certification portal.
- Full access to all course materials and slide decks
- Hands-on lab access on Rocheston Rose X OS environment
- Access to Rocheston CyberNotes
- Access to Rocheston Zelfire — EDR/XDR SIEM platform
- Access to Rocheston Raven — online cyber range exercise platform
- Access to Rocheston Vulnerability Vines AI