Blockchain Mining with Machine Learning
Introduction
Blockchain technology is becoming increasingly popular. As a decentralized system, it could enhance trust, security, transparency, and traceability of data across a business network. To mine a block, miners must search for a nonce that meets the defined criteria, and there has been a long-held belief that brute force is the only feasible and profitable mining strategy. This resource-based competition has therefore led to excessive energy consumption and severe environmental issues.
The project aims to explore the use of machine learning in blockchain mining. More specifically, it introduces the application of machine learning to 1) enhance nonce finding, 2) optimize transaction selection, and 3) discover chain-level mining strategies. Through developing a more efficient and sustainable block mining strategy, it is hoped that this work will encourage miners to adopt more environmentally conscious mining methods and pave the way for a greener future in blockchain mining.
3-minute Video
Supervisor
Professor Liu, Qi
BSc Shandong University; MS National University of Singapore; PhD University of Oxford
Assistant Professor at the University of Hong Kong
Fax: (+852) 2559 8447
Email: liuqi@cs.hku.hk
Homepage: https://leuchine.github.io/
Group Member
Cheung Yau Shing Jonathan (3035783560)
BASc(FinTech)
u3578356@connect.hku.hk