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shield-checkSecurity & Performance

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2.4 Security & Performance shield-check

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.

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a. Fraud Detection (AI Anomaly Scoring) brain-circuit

  • 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.

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b. Access Control & Authentication Layers joystick

  • 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.

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

  • 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.

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d. Performance Benchmarks chart-waterfall

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.

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