Decentralized Fraud Detection in Crypto Exchanges

Objectives to cover:

1. Introduction: Overview of exchanges, decentralized challenges, and fraud detection needs.
2. DEX Features: Comparing centralized exchanges and fraud in DEXs.
3. Data Mining: Relevance to crypto and blockchain challenges.
4. Algorithms: Classification, clustering, graph-based, and ML models.
5. Data Mining in DEXs: Case studies, metrics, and blockchain integration.
6. Smart Contracts: Privacy, scalability, and security.
7. Effectiveness: Metrics, comparisons, and limitations.
8. Future: AI, decentralized IDs, and crypto security.
9. Conclusion: Insights and opportunities in DEX fraud detection.

Reference:  APA style