Assess learners' ability to evaluate and compare homomorphic encryption, secure enclaves (TEEs), and differential privacy for deploying machine learning models in regulated environments; scope includes threat models, privacy–utility–performance trade-offs, scalability and latency impacts, integration and key/attestation management, measurement and auditing metrics, compliance implications (e.g., GDPR, HIPAA), and recommending practical or hybrid solutions with mitigation strategies and documentation for regulators.