Explainable AI for Anomaly Detection in Blockchain Microtransactions

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This research focuses on a novel Blockchain-based Explainable AI (XAI) framework to address challenges in fraud detection. It explores the current landscape, including deep autoencoders, graph neural networks, and integration of explainability. The methodology includes blockchain data preprocessing, anomaly detection models, and tools like SHAP and LIME for interpretability. Validation incorporates performance metrics, expert feedback, and interactive dashboards. The study delivers actionable...