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E. M. Ali Qhal

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Review Open access Aug 2026

AI-Driven Unsupervised Framework for Detecting and Analyzing Anomalous Cryptocurrency Transactions Across Blockchain Networks Using Multi-Feature Analysis

An AI-driven framework for detecting anomalous transactions in cryptocurrency datasets using unsupervised learning techniques, specifically the Isolation Forest algorithm, demonstrates that unsupervised AI methods provide a robust, adaptive, and scalable solution for proactive fraud detection in blockchain networks.

E. M. Ali Qhal · 0 citations

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