RealAssetChain
  • RealAsset Chain (RAC) Whitepaper
  • Preface
  • I. Project Overview and Strategic Vision
    • 1.1 Strategic Positioning and Core Vision of RealAsset Chain (RAC)
    • 1.2 Industry Innovation Through the Integration of Blockchain and Real World Assets (RWA)
    • 1.3 RAC's Differentiation Strategy and Core Value Proposition
  • II. Market Analysis
    • 2.1 Global Macroeconomic Environment and RWA Allocation Trends
    • 2.2 Market Segmentation and Growth Potential in the RWA Sector
    • 2.3 Challenges and Opportunities in the Digital Transformation of Traditional Financial Assets
    • 2.4 Blockchain as an Innovation Driver for the RWA Market
    • 2.5 Analysis of Industry Leaders and Competitive Landscape Assessment
    • 2.6 Regulatory Landscape and Policy Trend Analysis
  • III. Technological Innovation Architecture
    • 3.1 Core Blockchain Technology Selection and Optimization Strategy for RAC
    • 3.2 On-chain Issuance, Trading, and Settlement Mechanism for RWA Assets
    • 3.3 Cross-chain and Interoperability Solutions
    • 3.4 Data Privacy Protection and Security Framework
    • 3.5 Oracles and the Reliability of Off-chain Data
    • 3.6 Scalability and Network Security Optimization Strategy
  • IV. RAC Business Model
    • 4.1 Core Business Logic and Asset Selection Criteria of RAC
    • 4.2 Diversified RWA Asset Categories and Management Models
    • 4.3 Coordination Mechanism Between On-chain and Off-chain Assets
  • V. Tokenomics Design
    • 5.1 RAC Token Economy and Value Circulation Model
    • 5.2 Total Token Supply, Deflationary Mechanisms, and Incentive Strategies
    • 5.3 Staking and Liquidity Mining Programs
    • 5.4 Governance Token Design and Community Incentive Plan
  • VI. Governance Structure and Risk Management
    • 6.1 Decentralized Autonomous Organization (DAO) and Decision-making Framework
    • 6.2 Risk Identification, Early Warning, and Control System
    • 6.3 Compliance Audits and Dynamic Regulatory Mechanisms
  • VII. Development Roadmap and Phase Planning
  • VIII. Team Background and Advisory Board
  • IX. Risk Disclosure and Legal Statement
Powered by GitBook
On this page
  1. VI. Governance Structure and Risk Management

6.2 Risk Identification, Early Warning, and Control System

RAC emphasizes platform stability and asset security by integrating a smart, AI-powered risk management framework into its core infrastructure. This enables proactive threat detection, real-time alerts, and automated intervention.

1. Risk Identification System

RAC's risk engine integrates on-chain behavior analysis, user modeling, price volatility tracking, and oracle verification to train its AI risk models. Key focus areas include:

  • Abnormal large transfers (Anti-whale detection)

  • Flash loan exploits

  • Spikes in smart contract call frequency

  • Sudden liquidity withdrawal events (LP Panic Exit)

2. Real-Time Alert Model

The AI system performs second-level analysis of on-chain data and classifies risk into:

  • Green: Safe and normal behavior

  • Yellow: Mild anomalies flagged for monitoring

  • Red: High-risk behavior; system triggers freeze + manual review

Cross-module integration ensures that, for example, an oracle data anomaly can trigger transaction throttling or contract-level execution restrictions.

3. Control and Response Mechanisms

  • Multi-signature access control for critical operations (e.g., upgrades, unlocks)

  • DAO fallback protocols such as on-chain asset recovery votes

  • Time-lock execution layers for high-risk transactions, enabling delay and community alerts

4. User Risk Visibility

Users can monitor their account and asset risk levels in real time via the RAC wallet or dashboard. Personalized risk alerts can be set (e.g., transaction limits, LP withdrawal warnings).

Previous6.1 Decentralized Autonomous Organization (DAO) and Decision-making FrameworkNext6.3 Compliance Audits and Dynamic Regulatory Mechanisms

Last updated 7 days ago