Course · AI Security & Governance
MITRE ATLAS: Securing AI Systems Against Adversarial Attacks
ATT&CK gave defenders a shared language for network intrusions. ATLAS does the same for machine learning — poisoning, evasion, model theft and inference attacks. This course teaches you to threat-model an AI system the way an adversary reads it.
MITRE ATLASData poisoningEvasionModel theftThreat modelingAI IR
What you will be able to do
- Navigate the MITRE ATLAS matrix: tactics, techniques and real-world case studies of AI compromise
- Threat-model a machine learning pipeline from data collection through inference and monitoring
- Understand data poisoning and backdoor attacks, and the provenance controls that stop them
- Test evasion and adversarial-example robustness against your own models
- Defend against model extraction, membership inference and training-data leakage
- Build ATLAS-mapped detections and an AI incident response plan your team can rehearse
Who this course is for
ML and data engineers who now own security for their models
Security architects assessing AI systems
Red teamers moving into adversarial machine learning
Course facts
- Level
- All Levels
- Platform
- Udemy — lifetime access, mobile and TV, 30-day refund
- Includes
- Downloadable resources, Q&A support and a certificate of completion
- Instructor
- Nexus Academy — cybersecurity, compliance, cloud and AI
Next step
Start MITRE ATLAS today
Enrol on Udemy and keep the course for life, or read the full briefing on this topic first.