Course Outline
Introduction to AI Threat Modeling
- Factors contributing to the vulnerability of AI systems
- Comparing the AI attack surface with traditional systems
- Key attack vectors across data, model, output, and interface layers
Adversarial Attacks on AI Models
- Comprehending adversarial examples and perturbation techniques
- Distinguishing between white-box and black-box attacks
- Exploring FGSM, PGD, and DeepFool methods
- Visualizing and generating adversarial samples
Model Inversion and Privacy Leakage
- Inferring training data from model outputs
- Understanding membership inference attacks
- Assessing privacy risks in classification and generative models
Data Poisoning and Backdoor Injections
- Analyzing how poisoned data impacts model behavior
- Investigating trigger-based backdoors and Trojan attacks
- Strategies for detection and sanitization
Robustness and Defense Techniques
- Adversarial training and data augmentation methods
- Gradient masking and input preprocessing techniques
- Model smoothing and regularization approaches
Privacy-Preserving AI Defenses
- Introduction to differential privacy
- Noise injection mechanisms and managing privacy budgets
- Federated learning and secure aggregation protocols
AI Security in Practice
- Threat-aware model evaluation and deployment procedures
- Applying ART (Adversarial Robustness Toolbox) in practical scenarios
- Industry case studies: analyzing real-world breaches and mitigations
Summary and Next Steps
Requirements
- A solid understanding of machine learning workflows and model training processes
- Proficiency in Python and experience with common ML frameworks such as PyTorch or TensorFlow
- Familiarity with fundamental security or threat modeling concepts is advantageous
Audience
- Machine learning engineers
- Cybersecurity analysts
- AI researchers and model validation teams
Custom Corporate Training
Training solutions designed exclusively for businesses.
- Customized Content: We adapt the syllabus and practical exercises to the real goals and needs of your project.
- Flexible Schedule: Dates and times adapted to your team's agenda.
- Format: Online (live), In-company (at your offices), or Hybrid.
Price per private group, online live training, starting from 3200 € + VAT*
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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
