Course Outline
Introduction to AI Threat Modeling
- Factors that make AI systems vulnerable.
- Comparing the AI attack surface with traditional IT systems.
- Key attack vectors across data, model, output, and interface layers.
Adversarial Attacks on AI Models
- Understanding adversarial examples and perturbation techniques.
- Distinguishing between white-box and black-box attacks.
- Exploring FGSM, PGD, and DeepFool methods.
- Techniques for visualizing and crafting adversarial samples.
Model Inversion and Privacy Leakage
- Methods for inferring training data from model outputs.
- Understanding membership inference attacks.
- Assessing privacy risks in classification and generative models.
Data Poisoning and Backdoor Injections
- The impact of poisoned data on model behavior.
- Trigger-based backdoors and Trojan attacks.
- Strategies for detection and data sanitization.
Robustness and Defense Techniques
- Adversarial training and data augmentation strategies.
- Gradient masking and input preprocessing methods.
- Model smoothing and regularization techniques.
Privacy-Preserving AI Defenses
- Introduction to differential privacy principles.
- Noise injection and managing privacy budgets.
- Federated learning and secure aggregation protocols.
AI Security in Practice
- Threat-aware model evaluation and deployment practices.
- Applying the ART (Adversarial Robustness Toolbox) in real-world scenarios.
- Industry case studies examining real-world breaches and mitigation efforts.
Summary and Next Steps
Requirements
- A foundational understanding of machine learning workflows and model training processes.
- Experience using Python and common machine learning frameworks such as PyTorch or TensorFlow.
- Familiarity with basic security or threat modeling concepts is advantageous.
Audience
- Machine learning engineers.
- Cybersecurity analysts.
- AI researchers and model validation teams.
Testimonials (2)
I really enjoyed learning about AI attacks and the tools out there to begin practicing and actively using for security testing. I took a lot of knowledge away which I didn't have at the beginning and the course met what I hoped it would be. My favorite part shown from the training was Comet Browser and was amazed at what it could do. Definitely something will be looking into more. Overall it was a great course and enjoyed learning all OWASP GenAI Top 10.
Patrick Collins - Optum
Course - OWASP GenAI Security
The profesional knolage and the way how he presented it before us
