What did we learn?
That's a wrap for now; but don't lose your passion for learning every day.
What we learned
We've brought you safely through the AI Cybersecurity Course.
A quick recap of the places we visited and practiced:
- Differences between AI Security and Traditional Security
- Reference Frameworks (OWASP ML/LLM Top 10, NIST AI RMF)
- Overview of Security Risks Associated with AI Systems
- Protecting Training Data and Models
- Training Risks: Data Poisoning
- Security in Model Deployment and Updates
- Adversarial Attacks and Model Evasion
- Prompt Injection Attacks and Model Manipulation
- Model Extraction and Theft (Model Stealing)
- Principles of Responsible and Transparent AI
- Privacy Risks in AI's Use of Personal Data
- Algorithmic Bias and Its Impact on Security and Trust
- Risk Assessment Before Adopting AI Solutions
- Continuous Monitoring and Auditing of AI Systems in Production
- Organizational Policies for the Secure Use of AI
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Thank you so much for joining us on this journey 🤘🏽