AI Security Blueprint - Healthcare Edition

Overview

Healthcare AI security operates under constraints no other industry faces: HIPAA compliance is mandatory, PHI protection is non-negotiable, and security failures can directly harm patients. Healthcare organizations are targeted by ransomware gangs who know that patient care creates urgency to pay. AI systems create new attack surfaces while processing data that attackers value highly.

This comprehensive security blueprint is built specifically for healthcare AI. It provides HIPAA-compliant security architecture, controls that protect PHI throughout AI lifecycles, and operational practices that defend against healthcare-targeted threats while enabling clinical AI innovation.

What's Inside

• Healthcare AI Threat Landscape: Healthcare-specific threat analysis covering ransomware targeting healthcare AI, attacks on clinical AI systems, PHI-focused attacks (training data theft, model inversion, membership inference), and supply chain threats through AI vendors
• HIPAA Security Requirements for AI: Mapping HIPAA Security Rule requirements to AI systems including administrative safeguards, physical safeguards, and technical safeguards specific to AI training, inference, and storage
• Security Architecture: Reference architecture for healthcare AI including network segmentation, EHR integration security, and clinical system connectivity patterns
• Access Control Framework: Role-based access control for AI systems aligned with minimum necessary principle, including controls for AI development, model access, and inference endpoints
• Data Protection: PHI protection across AI lifecycles including training data security, de-identification for AI development, encryption requirements, and secure data pipelines
• AI-Specific Security Controls: Healthcare-specific AI controls including adversarial attack protection for diagnostic AI, model integrity monitoring, and clinical decision support security
• Vendor Security Management: BAA requirements for AI vendors, third-party AI risk assessment, and ongoing vendor security monitoring
• Incident Response: Healthcare AI incident response including HIPAA breach notification integration, clinical AI compromise response, and ransomware playbooks for AI systems
• Compliance & Audit: Audit controls for AI systems, documentation requirements, and compliance monitoring

Who This Is For

• Healthcare CISOs responsible for security including AI systems
• Privacy Officers ensuring HIPAA compliance for AI
• Clinical Informatics teams deploying AI in clinical environments
• Health IT Security teams protecting AI infrastructure
• Compliance Officers managing AI vendor oversight

Why This Resource

Healthcare security frameworks often predate AI, and AI security frameworks often ignore healthcare requirements. This blueprint bridges both—providing security architecture that meets HIPAA requirements while addressing AI-specific threats.

Every control accounts for healthcare context: PHI protection is built into every layer, clinical systems receive special attention, and vendor management addresses the BAA complexity of AI services.

FAQ

Q: How do we protect PHI in AI training data?

A: Data protection covers the full PHI lifecycle in AI: de-identification strategies for training data, minimum necessary access controls, encryption requirements for data at rest and in transit, secure data pipeline architecture, and audit logging that satisfies HIPAA requirements.

Q: What about BAA requirements for AI vendors?

A: Vendor security management provides detailed guidance on BAA provisions for AI vendors: what additional terms are needed for AI services beyond standard BAAs, how to assess vendor AI security practices, and ongoing monitoring requirements for AI-related vendor risks.

Q: How do we defend clinical AI against adversarial attacks?

A: AI-specific security controls cover adversarial attack protection for healthcare AI: input validation for diagnostic AI, monitoring for adversarial inputs, model integrity checking, and incident response procedures for suspected adversarial attacks on clinical systems.