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Security Guideline Document

Security Guideline Document: Unity AI Beta Program

Version: 1.0
Date: October 26, 2023

1. Introduction

The Unity AI Beta Program establishes an open ecosystem connecting creators with AI tools for accelerated RT3D content creation. This document outlines security protocols to protect user data, AI models, and infrastructure, ensuring confidentiality, integrity, and availability (CIA triad) across global operations.

2. Security Objectives

  • Confidentiality: Protect user PII, AI models, and beta-test data.
  • Integrity: Ensure tamper-proof data processing and model training.
  • Availability: Maintain 99.9% uptime via scalable architecture.
  • Compliance: Adhere to GDPR, CCPA, and ISO/IEC 27001.

3. Technical Architecture & Security Zones

3.1 Architecture Overview

  • Frontend: React 18.2 (TLS 1.3 encrypted)
  • Backend: Microservices via Kubernetes 1.27 (AWS EKS)
  • AI Tooling: Isolated in Docker 23.0 containers
  • Data Storage: Multi-region AWS S3 with server-side encryption (SSE-S3)

3.2 Security Zones

Zone Components Access Controls
Public DMZ User registration portal, CDN (CloudFront) WAF, DDoS protection (AWS Shield)
Restricted Zone AI APIs (TensorFlow 2.12), Beta tools VPC Peering, Private Subnets
Data Vault PostgreSQL 15 (encrypted at rest), Redis 7 IAM roles, Secrets Manager

4. Authentication & Authorization

  • User Auth: OAuth 2.0/OIDC via Auth0 (MFA enforced for beta testers).
  • API Auth: JWT tokens (RS256 signatures) with 15-minute expiry.
  • RBAC Model:
    • Creators: Read-only AI tool access.
    • Beta Testers: Write access to sandboxed environments.
    • Admins: Least-privilege IAM policies.

5. Data Security

5.1 Data Classification

  • Tier 1 (Critical): User credentials, payment data.
  • Tier 2 (Sensitive): AI training datasets, beta feedback.
  • Tier 3 (Public): Documentation, non-PII analytics.

5.2 Encryption

  • In Transit: TLS 1.3 (frontend/backend), mTLS (microservices).
  • At Rest: AES-256 (S3, EBS), TDE (PostgreSQL).
  • Key Management: AWS KMS with automatic key rotation.

5.3 Anonymization

  • PII pseudonymization via AWS Glue 4.0 before AI processing.

6. Network Security

  • Perimeter: Cloudflare WAF rules (OWASP Top 10 mitigation).
  • Internal:
    • NSG rules blocking east-west traffic by default.
    • Network segmentation (VLANs for dev/test/prod).
  • Monitoring: AWS GuardDuty + Suricata IDS.

7. AI Model Security

  • Model Isolation: AI tools run in gVisor-sandboxed containers.
  • Input Validation: Reject unstructured data >50MB; scan for malware (ClamAV).
  • Adversarial Defense: Model poisoning detection via Seldon Core 1.15.

8. Beta Program Security Controls

  • Access Governance:
    • Time-bound beta invites (72-hour validity).
    • Just-in-time (JIT) provisioning via Azure AD.
  • Environment:
    • Ephemeral test clusters (auto-destroyed after 48h).
    • AI tool outputs logged to SIEM (Splunk 9.0).

9. Incident Response

  • Phases:
    1. Detection: SIEM alerts (threshold: 3 failed logins/minute).
    2. Containment: Auto-isolate compromised containers.
    3. Eradication: Rotate keys, patch CVE within SLA (critical: 4h).
    4. Recovery: Restore from geo-redundant backups.
  • Reporting: Notify impacted users within 72h (per GDPR).

10. Compliance & Audit

  • Regulatory Alignment:
    • GDPR/CCPA: Data residency in EU/US regions; user consent workflows.
    • ISO 27001: Annual audits + automated compliance checks (AWS Config).
  • Penetration Testing: Quarterly scans via Synk/Vercara.

11. Security Training

  • Developers: Secure coding (OWASP ASVS) + AI ethics workshops.
  • Beta Testers: Phishing simulation (KnowBe4) + data handling guidelines.

12. Conclusion

This framework ensures the Unity AI Beta Program operates securely at scale. All controls will be reviewed biannually or after major releases.

Document Length: 3,150 characters
Approvals: CISO, Lead Architect