Compliance, Security & Trust
Zero-trust architecture, FedRAMP High, and ethical AI principles that enable government deployment
Chapter Highlights
Zero-Trust Architecture
Never trust, always verify with defense-in-depth
Elite Certifications
FedRAMP High, IL5/IL6, SOC 2, ISO 27001, HIPAA
Responsible AI
Fairness, transparency, accountability, privacy by design
10.1Security Architecture
Zero-Trust Principles
Core Tenets
Defense in Depth
Layer 1: Perimeter
✓ Firewalls
✓ IDS/IPS
✓ DDoS protection
✓ Web application firewall
Layer 2: Network
✓ Network segmentation
✓ VLANs
✓ Access control lists
✓ Traffic inspection
Layer 3: Application
✓ Secure coding practices
✓ Input validation
✓ Output encoding
✓ Session management
Layer 4: Data
✓ Classification
✓ Encryption
✓ Tokenization
✓ Rights management
10.2Certifications
Government Certifications
FedRAMP High
Scope
Cloud services for federal agencies
Controls
421 security controls
Audit
Annual assessment
Timeline
12-18 months
Impact Level 5 (IL5)
Scope
DoD controlled unclassified info
Requirements
232 controls
Environment
Dedicated infrastructure
Clearance
Secret level required
Impact Level 6 (IL6)
Scope
DoD classified information
Requirements
Physical isolation
Environment
SIPR/JWICS networks
Clearance
TS/SCI required
Commercial Certifications
SOC 2 Type II
- • Security, availability, integrity
- • Annual with continuous monitoring
- • Available under NDA
- • All production systems
ISO 27001
- • Information security mgmt
- • Annual surveillance
- • 3-year certification cycle
- • Global operations
HIPAA
- • Protected health information
- • Admin, physical, technical
- • Annual risk assessment
- • Business associate agreements
10.3Data Governance
Data Classification
Marketing materials • Published reports • Open source code
Employee communications • Non-sensitive business data • Development environments
Customer data • Financial information • Proprietary algorithms
Classified government data • Critical infrastructure • National security information
Data Lifecycle Management
Collection
- ✓ Purpose limitation
- ✓ Data minimization
- ✓ Consent management
- ✓ Legal basis documentation
Processing
- ✓ Access controls
- ✓ Audit logging
- ✓ Change tracking
- ✓ Version control
Storage
- ✓ Retention policies
- ✓ Geographic restrictions
- ✓ Backup procedures
- ✓ Archive management
Deletion
- ✓ Secure deletion
- ✓ Certificate of destruction
- ✓ Audit trail
- ✓ Compliance verification
10.4Responsible Use Narrative
Ethical AI Principles
Fairness
- ✓ Bias detection and mitigation
- ✓ Algorithmic auditing
- ✓ Diverse training data
- ✓ Regular fairness testing
Transparency
- ✓ Explainable AI
- ✓ Model cards
- ✓ Decision documentation
- ✓ Audit trails
Accountability
- ✓ Human-in-the-loop
- ✓ Override mechanisms
- ✓ Appeal processes
- ✓ Responsibility assignment
Privacy
- ✓ Federated learning
- ✓ Synthetic data
- ✓ Privacy-preserving techniques
- ✓ Consent management
Use Case Restrictions
Prohibited Uses
✗ Mass surveillance
✗ Social credit scoring
✗ Discriminatory profiling
✗ Autonomous weapons
Restricted Uses (with oversight)
• Law enforcement (with oversight)
• Healthcare decisions (clinician review)
• Financial decisions (appeal process)
• Employment screening (human review)
Summary: Security & Trust Essentials
Zero-trust architecture: Never trust, always verify with defense-in-depth across 4 layers
Elite certifications: FedRAMP High, IL5/IL6, SOC 2 Type II, ISO 27001, HIPAA
Data governance: 4-level classification (Public → Internal → Confidential → Secret/TS)
Ethical AI principles: Fairness, transparency, accountability, privacy by design
Use case restrictions: Prohibited (mass surveillance) vs. Restricted with oversight (law enforcement)
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