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Course 09 · Advanced
AI Cybersecurity, Privacy and Digital Infrastructure
Securing AI systems and using AI for security: adversarial threats, prompt injection, data leakage, privacy engineering and resilient infrastructure.
Learning outcomes
- ◆Threat-model an LLM-powered application
- ◆Mitigate prompt injection, data poisoning and leakage
- ◆Apply privacy-by-design and data minimisation
- ◆Plan AI incident detection and response
14-week syllabus
- Week 1The AI threat landscape
- Week 2Threat modelling AI systems
- Week 3Prompt injection and jailbreaks
- Week 4Data poisoning and model theft
- Week 5Privacy engineering and anonymisation
- Week 6AI for security operations
- Week 7Identity, access and secrets management
- Week 8Midterm examination
- Week 9Cloud and infrastructure security for AI
- Week 10Supply chain security for models
- Week 11Red-teaming and evaluation
- Week 12Incident response for AI
- Week 13Regulation: NIS2, GDPR and sectoral rules
- Week 14Capstone: secure AI architecture and final examination