Timeline analysis Monitoring and Detection
RCCE students will learn digital forensics acquisition, evidence handling, timeline reconstruction, memory and disk analysis, and forensic reporting. RCCE students will learn to collect and preserve digital evidence following forensically sound procedures, reconstruct attack timelines from multiple artifact sources, perform forensic analysis on endpoints, memory, networks, and cloud environments, and produce investigation reports that withstand legal and regulatory scrutiny. This monitoring course teaches comprehensive detection and observability strategies for proactive security operations. Starting from foundational concepts, 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 Timeline analysis Monitoring and Detection
- Monitor and audit privilege usage; detect escalation attempts
- Execute hands-on tasks for lab series
- Execute hands-on tasks for level: advanced
- Explain Track: Foundations fundamentals
- Explain Course Overview fundamentals
- Design a scalable privilege management architecture with policy and enforcement
- Build detections and response workflows for privilege escalation, including AI-specific attack surfaces.
- Execute hands-on tasks for learning objectives
- Explain AI/ML System Architecture Overview fundamentals
- Monitor and audit privilege usage; detect escalation attempts, including Data integrity validation at ingestion.
- Execute hands-on tasks for ai/ml threat landscape
- Execute hands-on tasks for data poisoning
| Module 01 | AI Monitoring and Detection |
| Module 02 | Lab Series |
| Module 03 | Level: Advanced |
| Module 04 | Track: Foundations |
| Module 05 | Course Overview |
| Module 06 | AI Threat Modeling |
| Module 07 | Detection Engineering |
| Module 08 | Learning Objectives |
| Module 09 | AI/ML System Architecture Overview |
| Module 10 | Security Monitoring Touchpoints |
| Module 11 | AI/ML Threat Landscape |
| Module 12 | Data Poisoning |
| Module 13 | Model Evasion |
| Module 14 | Model Extraction |
All hands-on labs run on Rocheston Rose X OS. Students practice timeline analysis monitoring and detection 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: Execute hands-on tasks for lab series
- Lab 3: Execute hands-on tasks for level: advanced
- Lab 4: Explain Track: Foundations fundamentals
- Lab 5: Explain Course Overview fundamentals
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for Timeline analysis Monitoring and Detection, 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