MetaUser DAO_ White Paper
MetaUserDAO WhitePaper
MetaUserDAO WhitePaper
  • Introduction
  • Project Overview
    • MUD's Solutions and Advantages
    • Ecosystem Strategy and Business Model
  • Technical Architecture
    • Consensus and Core: Cosmos SDK & Tendermint
    • Cross-Chain and Smart Contracts
    • AI-Powered Dynamic Tagging System
    • RWA Asset Mapping Protocol
    • MUD Distributed Storage System (MDN)
    • MUD Oracle Network (MON)
    • Hybrid Consensus and Proof Mechanisms
  • Network Governance and DAO Framework
    • Incentive and Deterrence Design
  • Token Economics and Governance
    • Stake incentive
  • Application Scenarios
    • Metaverse Identity and Immersive Economy
    • Real-World Asset Tokenization
    • Cross-Chain Asset & Identity Coordination
    • Creator Economy and Decentralized Entertainment
  • Roadmap and Strategic Vision
  • Legal Disclaimer and Risk Disclosure
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On this page
  • IBC Protocol Integration
  • EVM Compatibility
  • AI-Powered Dynamic Tagging System
  • System Components
  • Core Algorithms
  • Privacy and Security
  1. Technical Architecture

Cross-Chain and Smart Contracts

IBC Protocol Integration

MUD implements the IBC protocol to interoperate with other Cosmos-based and non-Cosmos chains:

  • Heterogeneous chain interoperability (e.g., Ethereum, Bitcoin)

  • Cross-chain identity and credit transmission

  • RWA asset liquidity across chains

  • Synchronized state and data consistency

EVM Compatibility

MUD supports full compatibility with the Ethereum Virtual Machine:

  • Direct deployment of Solidity contracts

  • Supports Truffle, Hardhat, Remix, etc.

  • Standard Web3 JSON-RPC API

  • Optimized gas model for efficient execution

This dual-layer compatibility enables flexibility across Cosmos and Ethereum ecosystems.

AI-Powered Dynamic Tagging System

System Components

  • Data Collection Layer: Gathers on-chain behavior (transactions, holdings, interactions)

  • Analytics Layer: Uses machine learning models to assess behavior

  • Inference Engine: Produces credit scores and identity tags

  • Application Interface Layer: Provides APIs for querying and verification

Core Algorithms

  • Address clustering & anomaly detection

  • Gradient Boosted Decision Trees for creditworthiness

  • Random Forests for multi-dimensional scoring

  • Graph Neural Networks for relationship analysis

  • Reinforcement learning for adaptive modeling

Privacy and Security

  • Zero-knowledge proofs for privacy-preserving scoring

  • Data anonymization before storage

  • Differential privacy during analysis

  • Decentralized AI training and inference

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Last updated 11 days ago