Blockchain Intelligence: Methods, Applications and Challenges

Zibin Zheng, Hong-Ning Dai, Jiajing Wu

Research output: Book/ReportBook or reportpeer-review

2 Citations (Scopus)


This book focuses on using artificial intelligence (AI) to improve blockchain ecosystems. Gathering the latest advances resulting from AI in blockchain data analytics, it also presents big data research on blockchain systems. 

Despite blockchain’s merits of decentralisation, immutability, non-repudiation and traceability, the development of blockchain technology has faced a number of challenges, such as the difficulty of data analytics on encrypted blockchain data, poor scalability, software vulnerabilities, and the scarcity of appropriate incentive mechanisms. Combining AI with blockchain has the potential to overcome the limitations, and machine learning-based approaches may help to analyse blockchain data and to identify misbehaviours in blockchain. In addition, deep reinforcement learning methods can be used to improve the reliability of blockchain systems. 

This book focuses in the use of AI to improve blockchain systems and promote blockchain intelligence. It describes data extraction, exploration and analytics on representative blockchain systems such as Bitcoin and Ethereum. It also includes data analytics on smart contracts, misbehaviour detection on blockchain data, and market analysis of blockchain-based cryptocurrencies. As such, this book provides researchers and practitioners alike with valuable insights into big data analysis of blockchain data, AI-enabled blockchain systems, and applications driven by blockchain intelligence.

Original languageEnglish
Place of PublicationSingapore
PublisherSpringer Singapore
Number of pages175
ISBN (Electronic)9789811601279
ISBN (Print)9789811601262, 9789811601293
Publication statusPublished - 31 May 2021

Scopus Subject Areas

  • Computer Science(all)

User-Defined Keywords

  • blockchain
  • data mining
  • artificial intelligence
  • smart contract
  • machine learning


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