Secure Computing Infrastructure in Data AI
The Secure Computing Infrastructure is a key component of the Data AI platform, enabling privacy-preserving computations within Trusted Execution Environments (TEEs). It ensures that both Personal AIs and AI Agents can process sensitive user data securely while maintaining transparency, decentralization, and resistance to manipulation.
Core Layers of the Secure Computing Infrastructure:
Client Layer:
Manages user authentication, data submission, and retrieval.
Supports OAuth-based authentication for secure user verification.
Ensures data encryption during transmission to protect user privacy.
Allows users to securely retrieve processed data.
Chain Governance Layer:
Maintains on-chain transparency and security.
Manages user and node registration, verifying credentials and permissions.
Handles staking mechanisms to secure network participation.
Verifies TEE computation proofs to ensure execution integrity.
Distributes rewards based on task completion and penalizes malicious behavior.
Scheduler Layer:
Responsible for task distribution, workload balancing, and security monitoring.
Distributes computational tasks to available TEE nodes.
Balances workloads across nodes to maximize efficiency.
Monitors node performance and security to detect anomalies.
Verifies data integrity before processing and finalizing results.
TEE Node Layer:
Executes confidential computing tasks in a trusted and verifiable environment.
Initializes and connects secure TEE environments.
Executes assigned computations while ensuring data privacy.
Generates cryptographic proofs for task verification and auditability.
By integrating TEE-backed execution with blockchain-based validation, the Secure Computing Infrastructure ensures confidential AI computations with on-chain verifiability, efficient task execution, and a transparent governance model that rewards honest computation while penalizing malicious behavior.
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