Jiajing Wu – författare

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.

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.

This two-volume set CCIS 2264 and CCIS 2265 constitutes the refereed proceedings of the 6th International Conference on Blockchain and Trustworthy Systems, BlockSys 2024, held in Hangzhou, China, during July 12–14, 2024. The 34 full papers presented in these two volumes were carefully reviewed and selected from 74 submissions.

This two-volume set CCIS 2264 and CCIS 2265 constitutes the refereed proceedings of the 6th International Conference on Blockchain and Trustworthy Systems, BlockSys 2024, held in Hangzhou, China, during July 12–14, 2024. The 34 full papers presented in these two volumes were carefully reviewed and selected from 74 submissions.

Blockchain, a decentralized ledger technology based on cryptographic algorithms, ensures the creation of immutable and tamper-proof ledgers in decentralized systems. The transparent nature of blockchain allows public access to transaction records, providing unprecedented opportunities for blockchain data analytics and mining. The primary value of blockchain transaction data analytics lies in two aspects: 1) by delving into the details of blockchain transaction data, we can extensively explore various types of user behavior patterns and the evolutionary process of blockchain transaction networks; and 2) analyzing blockchain transaction data aids in identifying illicit activities, offering effective regulatory solutions for the establishment of a healthier blockchain ecosystem. This book focuses on data analytics based on network-based approaches, providing a comprehensive analysis of blockchain data analytics problems, key technologies, and future directions. Different from most existing book, this book takes a unique approach to blockchain data analysis research, focusing on data analytics based on network-based approaches. Leveraging network analysis methods, the book concentrates on three main aspects of blockchain transaction data analytics and mining: (1) transaction network modelling and pattern mining, including macro and micro-level account attributes, money laundering network patterns, and network evolution patterns; (2) account business classification, such as account label prediction based on graph neural networks; and (3) anomaly behavior identification, covering phishing detection, risk scoring, and transaction tracking. Designed as a valuable resource for students, researchers, engineers, and policymakers in various fields related to blockchain data analytics, this book holds significant importance for understanding blockchain transaction behavior and addressing the detection of illicit activities in the blockchain space.

Blockchain, a decentralized ledger technology based on cryptographic algorithms, ensures the creation of immutable and tamper-proof ledgers in decentralized systems. The transparent nature of blockchain allows public access to transaction records, providing unprecedented opportunities for blockchain data analytics and mining. The primary value of blockchain transaction data analytics lies in two aspects: 1) by delving into the details of blockchain transaction data, we can extensively explore various types of user behavior patterns and the evolutionary process of blockchain transaction networks; and 2) analyzing blockchain transaction data aids in identifying illicit activities, offering effective regulatory solutions for the establishment of a healthier blockchain ecosystem. This book focuses on data analytics based on network-based approaches, providing a comprehensive analysis of blockchain data analytics problems, key technologies, and future directions. Different from most existing book, this book takes a unique approach to blockchain data analysis research, focusing on data analytics based on network-based approaches. Leveraging network analysis methods, the book concentrates on three main aspects of blockchain transaction data analytics and mining: (1) transaction network modelling and pattern mining, including macro and micro-level account attributes, money laundering network patterns, and network evolution patterns; (2) account business classification, such as account label prediction based on graph neural networks; and (3) anomaly behavior identification, covering phishing detection, risk scoring, and transaction tracking. Designed as a valuable resource for students, researchers, engineers, and policymakers in various fields related to blockchain data analytics, this book holds significant importance for understanding blockchain transaction behavior and addressing the detection of illicit activities in the blockchain space.

The Metaverse seamlessly integrates the real world with the virtual world and allows avatars to engage in a broad range of activities including entertainment, social networking, and trading. In this book, we dive into the Metaverse by discussing how blockchains connect various Metaverse components, digital currencies, and blockchain-empowered applications in the virtual world. On the other hand, Web3 has also attracted considerable attention due to its uniquely decentralized characteristics. The digital economy, currently undergoing a rapid development, is a critical driver to highly efficient societies. It is imperative that we investigate how to use Web3 technologies to address the critical concerns encountered during the development of the digital economy by fully exploring Web3. In this book, we also share insights into the Web3-based ecosystem in the Metaverse; topics of interest include decentralized finance, digital assets, the asset-trading market, etc.Unlikemost works on the subject, this book mainly concentrates on insights and discussions regarding blockchain, the Metaverse and Web3. In other words, it focuses on using blockchain technologies to enable an ecosystem for both the Metaverse and Web3. Topics addressed include blockchain fundamentals, smart contracts, value circulation in the Metaverse, the connection between the Metaverse and Web3, the establishment of the Metaverse on the basis of blockchain technologies, decentralized autonomous organization, decentralized storage, digital economy, Web3-based economic systems for the Metaverse, etc.This book will be a valuable resource for students, researchers, engineers, and policymakers working in various areas related to blockchain, the Metaverse and Web3. We hope that it will also inspire readers from academia and industry alike, and ultimately help them create a truly open, fair, and rational ecosystem for the Metaverse and Web3.