NIST Standards & Compliance
Technical frameworks, security controls, and verification protocols that ensure Aevum Encyclopedia maintains the highest standards of data integrity, AI transparency, and user privacy.
Overview
Aevum Encyclopedia operates under a strict compliance architecture aligned with National Institute of Standards and Technology (NIST) publications. Our infrastructure, AI pipelines, and editorial workflows are continuously mapped to these frameworks to ensure reliability, security, and ethical operation.
NIST Cybersecurity Framework (CSF 2.0)
We implement the CSF 2.0 core functions across all infrastructure layers, from edge CDNs to database clusters and AI inference endpoints.
Implementation Status
Fully Implemented- Zero-trust network architecture
- Continuous vulnerability scanning
- Automated incident response runbooks
- Supply chain security controls
- Quarterly penetration testing
- Multi-region failover & recovery
Key Controls
Identity management uses OIDC/OAuth2 with hardware-backed MFA. Data in transit is protected via TLS 1.3 with HSTS. Storage encryption follows AES-256-GCM. All CI/CD pipelines enforce SBOM generation and container signing.
AI Risk Management Framework (AI RMF 1.0)
Our AI augmentation layer (search ranking, content synthesis, and fact-checking) is governed by the NIST AI RMF to mitigate hallucination, bias, and opacity risks.
Implementation Status
Fully Implemented- Model card transparency disclosures
- Adversarial testing & red-teaming
- Human-in-the-loop editorial review
- Output citation & source tracing
- Bias impact assessments
- Versioned model rollbacks
Technical Safeguards
All generative outputs are constrained via retrieval-augmented generation (RAG) over our verified knowledge graph. Confidence scoring thresholds (≥0.92) gate public visibility. Uncertain claims are routed to expert moderators before publication.
NIST Privacy Framework
User data handling, consent management, and cross-border data flows comply with the NIST Privacy Framework core functions: TCI, DFI, ARA, TPF, CMM, and LEX.
Implementation Status
In Progress (92%)- Data minimization & purpose limitation
- Explicit consent granular controls
- Right to erasure & portability APIs
- Privacy impact assessments (PIAs)
- Third-party vendor assessments
Compliance Notes
We maintain GDPR, CCPA, and LGPD alignment. Personal identifiers are hashed or pseudonymized. Analytics use privacy-preserving techniques (k-anonymity, differential privacy) where applicable.
Data Standards & Metadata
Knowledge entries follow standardized schemas to ensure interoperability, machine readability, and long-term archival viability.
Schema Alignment
- Dublin Core / Schema.org: Core metadata fields for discovery
- NISO Z39.85: Crosswalking and controlled vocabularies
- NIST SP 800-131A: Cryptographic standards for data-at-rest
- W3C RDF/SPARQL: Knowledge graph serialization
Export formats include JSON-LD, XML (TEI-compliant for humanities), and CSV. All datasets include provenance tracking via W3C Provenance Ontology.
Auditing & Transparency
Compliance is not static. We maintain continuous verification through automated checks and independent review.
Audit Cadence
| Scope | Frequency | Method | Status |
|---|---|---|---|
| Infrastructure Security | Quarterly | Third-party pen test | Pass |
| AI Output Integrity | Monthly | Automated evaluation suite | Pass |
| Privacy Compliance | Semi-annually | Legal & technical review | In Review |
| Editorial Accuracy | Continuous | Peer moderation + AI verification | Pass |
Transparency reports are published annually. Request detailed audit summaries via compliance@aevumencyclopedia.org.
References & External Documentation
| Framework / Standard | Publication | Link |
|---|---|---|
| Cybersecurity Framework 2.0 | NIST CSF 2.0 | nist.gov/cyberframework |
| AI Risk Management Framework | NIST AI RMF 1.0 | nist.gov/itl/ai-rmf |
| Privacy Framework | NIST Privacy Framework | nist.gov/privacy-framework |
| Cryptographic Standards | SP 800-131A Rev 2 | csrc.nist.gov/sp800-131a |