AI-Driven Threats and Defenses

This unit explores how generative AI and machine learning transform the cyber threat landscape and the defenses used to mitigate those threats across sectors such as business and healthcare. Students build on foundational cybersecurity concepts to assess AI-enabled attacks, evaluate hardware and human risks, and prepare ethical, legal, and technical mitigation strategies for subsequent applied units.

Learning Objectives

• Analyze how generative AI and machine learning techniques enable new cyber threats (e.g., polymorphic malware, accelerated password cracking, and deepfakes) using sector-specific examples such as healthcare and enterprise environments
• Evaluate vulnerabilities introduced at the human, software, and hardware layers by AI adoption and prioritize mitigation strategies based on likelihood, impact, and feasibility
• Demonstrate the design of an AI-informed layered defense scenario by selecting and justifying AI-enabled detection and response controls (e.g., analytics, anomaly detection, secure hardware considerations) for a given organization
• Apply ethical, legal, and regulatory frameworks to assess privacy and governance implications of AI in healthcare and recommend policy or technical controls to reduce harm and support compliance