Machine Learning for Blockchain Data Analysis: Progress and Opportunities

arXiv:2404.18251v1 Announce Type: cross
Abstract: Blockchain technology has rapidly emerged to mainstream attention, while its publicly accessible, heterogeneous, massive-volume, and temporal data are reminiscent of the complex dynamics encountered during the last decade of big data. Unlike any prior data source, blockchain datasets encompass multiple layers of interactions across real-world entities, e.g., human users, autonomous programs, and smart contracts. Furthermore, blockchain's integration with cryptocurrencies has introduced financial aspects of unprecedented scale and complexity such as decentralized finance, stablecoins, non-fungible tokens, …

abstract analysis arxiv attention big big data blockchain cs.cr cs.lg data data analysis datasets dynamics interactions machine machine learning massive multiple opportunities prior progress technology temporal type while world