Security & Performance

2.4 Security & Performance

The Security & Performance framework of Green Token is designed to ensure trust, compliance, and scalability across all ecosystem participants. By integrating AI-driven fraud detection, strict access control, and adherence to global compliance standards, the system achieves enterprise-grade reliability while maintaining smooth performance for end-users.

a. Fraud Detection (AI Anomaly Scoring)

  • Anomaly Detection Models: AI continuously monitors user behavior to detect suspicious patterns (e.g., repeated uploads, GPS spoofing, or duplicate tasks).

  • Dual Verification: Cross-checking of image/video input with geo-time metadata prevents fraudulent claims.

  • Adaptive Learning: Machine learning models evolve with new fraud vectors, improving accuracy over time.

  • Audit Trails: All flagged anomalies are logged immutably for transparency and review.

b. Access Control & Authentication Layers

  • Role-Based Access Control (RBAC): Distinguishes between user, partner, and admin permissions.

  • Multi-Factor Authentication (MFA): Required for enterprise and municipal partners accessing dashboards.

  • Secure APIs: Authentication tokens and encrypted API keys regulate partner integrations.

  • Data Segmentation: Sensitive user data is anonymized, ensuring only aggregated insights are shared with third parties.

c. Compliance Standards (ISO/IEC 27001, GDPR, PDPA)

  • ISO/IEC 27001: The system follows globally recognized standards for information security management.

  • GDPR (Europe): Provides data rights such as consent, erasure, and data portability for EU users.

  • PDPA (Thailand): Aligns with local data protection regulations, ensuring legal operation in key markets.

  • Privacy by Design: Compliance is embedded into the architecture, ensuring security at every layer.

d. Performance Benchmarks

Green Token is engineered to operate reliably at scale, ensuring both low latency and high concurrency without compromising verification accuracy.

  • Verification Latency: AI-powered MRV processes complete in under 1.5 seconds per action, providing near-instant user feedback.

  • Scalability: The Kubernetes-ready infrastructure supports over 500,000 concurrent users, proven in stress-testing environments.

  • Uptime & Reliability: Targeted system uptime of 99.95%, with automatic failover and load balancing.

  • Efficiency: Cloud-native deployment optimizes resource usage, minimizing environmental footprint of the system itself.

PreviousBlockchain & Government layerNextOur Roadmap

Last updated