Welcome to the workshop!
Workshop
In ProgressWelcome to Designing Secure ML Systems: A Threat Modeling and Risk Mitigation Lab
Today's icebreaker:
Security blind spots: What gets missed?
What’s one security risk you think often gets overlooked in ML systems?
Share your response in the chat!
Today's agenda:
- **Review:**Recap key concepts.
- **Demo:**Security walkthrough
- **Practice:**Securing the PackSure ML system.
- **Closing:**Key takeaways and next steps.
Today's learning objectives:
- Analyse vulnerabilities across the ML system lifecycle, mapping them to core security principles.
- Design secure ML workflows that address identified risks, including infrastructure, API, and model-level threats.
- Apply threat modelling techniques to a real-world ML scenario, identifying mitigation strategies at each stage.
- Develop basic team protocols for monitoring, incident response, and continuous security assessment.