Prerequisites: Solid ML & Python skills

What You'll Learn

• Advanced Attack Implementation

  Implement sophisticated evasion attacks (C&W, PGD) and data poisoning strategies.

• Defense Mechanisms

  Apply and analyze advanced defense techniques like adversarial training and certified defenses.

• Model Inference Attacks

  Understand and execute membership inference, attribute inference, and model stealing attacks.

• Robustness Evaluation

  Rigorously evaluate model security using standard benchmarks and adaptive attack strategies.

• Domain-Specific Adversarial ML

  Analyze adversarial threats specific to domains like computer vision and natural language processing.

• Practical Implementation

  Gain hands-on experience using frameworks like ART or CleverHans for attack and defense simulation.