Machine learning in/for blockchain: Future and challenges

被引:22
|
作者
Chen, Fang [1 ]
Wan, Hong [2 ]
Cai, Hua [1 ]
Cheng, Guang [3 ]
机构
[1] Purdue Univ, Dept Ind Engn, W Lafayette, IN 47906 USA
[2] North Carolina State Univ, Dept Ind & Syst Engn, Raleigh, NC 27695 USA
[3] Purdue Univ, Dept Stat, W Lafayette, IN 47906 USA
基金
美国国家科学基金会;
关键词
Bitcoin; blockchain; deep learning; machine learning; reinforcement learning; HEALTH-CARE; TECHNOLOGY;
D O I
10.1002/cjs.11623
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Machine learning and blockchain are two of the most notable technologies of recent years. The first is the foundation of artificial intelligence and big data analysis, and the second has significantly disrupted the financial industry. Both technologies are data-driven, and thus there are rapidly growing interests in integrating both for more secure and efficient data sharing and analysis. In this article, we review existing research on combining machine learning and blockchain technologies and demonstrate that they can collaborate efficiently and effectively. In the end, we point out some future directions and expect more research on deeper integration of these two promising technologies.
引用
收藏
页码:1364 / 1382
页数:19
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