Apprentice
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Adversarial ML & Security Threats
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Module 3: Making Models Robust

Module 3: Making Models Robust

by NSTC NSTC

July 4, 2026

About Module 3: Making Models Robust

Module Content

Module 3: Making Models Robust

12 Lessons

Chapter 3.1: Adversarial Training Techniques

Lesson 1: Techniques for generating adversarial examples

Lesson 2: Implementing adversarial training in ML pipelines

Lesson 3: Benefits and challenges of adversarial training

Chapter 3.2: Input Preprocessing and Gradient Masking

Lesson 1: Input transformations to prevent attacks

Lesson 2: Gradient masking and its effectiveness in defense

Lesson 3: Combining input preprocessing with adversarial training

Chapter 3.3: Certified Defenses and Formal Guarantees

Lesson 1: Introduction to certified defenses and robustness

Lesson 2: Formal methods for ensuring model security

Lesson 3: Challenges in proving robustness

Chapter 3.4: Evaluation Metrics for Robustness

Lesson 1: Defining evaluation metrics for adversarial robustness

Lesson 2: Attack success rate and model accuracy trade-offs

Lesson 3: Benchmarking and real-world evaluation strategies

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