Python Machine Learning - FRAUD-X: An Integrated AI, Blockchain, and Cybersecurity - ClickMyProject

Описание: Online financial fraud poses significant challenges, especially in mid-sized markets like North Macedonia, where rapid digital adoption in BFSI sectors outpaces security infrastructure development. This paper presents FRAUD-X, an integrated framework combining AI-based anomaly detection, blockchain-enabled transaction verification, cybersecurity intrusion detection, and real-time early warning systems. Evaluated on three datasets—including local anonymized BFSI transactions—FRAUD-X achieves a 2–4% F1-score improvement over single-layer AI models and maintains approximately 90% recall for zero-day threats. Key innovations include a permissioned blockchain for immutable transaction records, dynamic risk scoring through AI-cybersecurity integration, and real-time alerts that cut response times from hours to minutes. Operating efficiently at ~15–16 ms per transaction with moderate CPU usage, FRAUD-X supports near-real-time processing. Ablation studies validate the importance of each component, while security analyses demonstrate resilience against node compromises and advanced threats. FRAUD-X offers a practical, scalable solution for fraud detection in mid-scale BFSI markets, balancing high accuracy with operational feasibility.


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