2.0 Learning Outcomes

By the end of this chapter, students will be able to:

• Identify the concept of threat modelling in machine learning security.
• Identify different threat scenarios and attack surfaces in ML systems.
• Classify ML threats based on adversarial capabilities, knowledge, and intent.
• Apply common threat modelling frameworks to assess ML vulnerabilities.
• Identify the key actors, including adversaries and defenders.
• Differentiate between reactive and anticipatory security design
• Analyze diverse types of attacks and their impact on system security.
• Demonstrate understanding through case study analysis and scenario-based problem-solving.