Автор: Zibin Zheng, Hong-Ning Dai
Издательство: Springer
Год: 2021
Страниц: 170
Язык: английский
Формат: pdf (true), epub
Размер: 23.0 MB
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.
The goal of this book concentrates on using AI to improve blockchain ecosystem. We name the intelligence bestowed by AI to blockchain as blockchain intelligence. The blockchain intelligence is essentially the integration of AI, big data analytics, and blockchain technologies. Gathering latest advances brought by AI in data analytics of blockchain data, this book also fosters the big data research on blockchain systems.
This book describes data extraction, exploration, and analytics on representative blockchain systems such as Bitcoin and Ethereum. It also includes data analytics on smart contracts, misbehavior detection on blockchain data, and market analysis of blockchain-based cryptocurrencies. Moreover, this book also outlines future directions in blockchain intelligence. This book provides both researchers and practitioners with valuable insights into big data analytics of blockchain data, AI-enabled blockchain systems, and applications driven by blockchain intelligence.
Artificial intelligence (AI) as a broad discipline covering machine learning and cognitive computing is an ability of intelligent agents conducting intellectual tasks. The recent advances in big data, AI technologies (such as deep neural networks), and general purpose computer hardware such as graphic processing units (GPUs) have greatly driven the development of AI. Consequently, we have witnessed the proliferation of diverse AI applications such as computer vision, natural language processing, speech recognition, and sentimental analysis. Big data plays a critical role in propelling AI as well as AI applications. For example, deep learning mainly based on deep neural networks (DNNs) has achieved superior performance thanks to the availability of massive data so that DNNs can extract (or learn) enough features from large volumes of data.
Скачать Blockchain Intelligence: Methods, Applications and Challenges