Blockchain Transaction
Blockchain transaction analysis focuses on understanding and improving the security, efficiency, and privacy of transactions within blockchain networks. Current research heavily utilizes machine learning, employing models like graph neural networks, transformers, and recurrent neural networks to detect anomalies (e.g., fraud, money laundering), predict trends, and enhance overall network security. This research is crucial for bolstering trust in blockchain technology and its widespread adoption across various sectors, from finance to supply chain management. The development of robust and explainable AI methods for blockchain analysis is a key area of ongoing investigation.
Papers
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