🏗️ 5.Technical Architecture

🧠 Deep Learning Engine

Trained on large-scale on-chain datasets to accurately detect anomalies and potential attack patterns.

🔎 Adaptive Threat Detection System

Continuously adjusts detection logic based on evolving on-chain behaviors and threats.

📊 Intelligent Data Correlation Analysis

Cross-analyzes multiple dimensions (transaction patterns, contract activities, asset flows) to improve detection accuracy.

🌐 High-Frequency On-Chain Data Capture

Real-time synchronization of key blockchain data like transactions, contract calls, and event logs.

⚙️ Edge Computing Optimization

Preliminary local data processing to reduce central server load and increase speed.

🔗 Data Integrity Verification Mechanism

Cross-validation across multiple nodes ensures data authenticity and immutability.

🤖 User-Defined Rule Engine

Enables users to set automatic execution conditions like asset transfers or risk adjustments.

🔄 On-Chain Task Scheduling System

Executes tasks based on priority and gas fee optimization for maximum efficiency.

🛠️ Emergency Response Mechanism

Instantly triggers actions like freezing assets, revoking approvals, or transferring assets during critical threats.

🌎 Global Distributed Node Deployment

🛡️ Multi-Node Consensus Audit

High-risk activities are validated through node consensus before being flagged or intercepted.

📡 Node Reputation Scoring System

Dynamically adjusts node privileges and incentives based on audit accuracy and response speed.

🔗 Synchronized Monitoring Across Multiple Chains

🌉 Lightweight Cross-Chain Bridge Integration

Efficient synchronization of asset states and risk events across different blockchains.

🧩 Unified Cross-Chain Data Standards

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