Blockchain technology has received extensive attention recently due to its provision of secure and decentralized resource sharing manner. Despite the merits of decentralization, immutability, non-repudiation and traceability of blockchain, the development of blockchain technology has undergone a number of challenges such as difficulty of data analytics on encrypted blockchain data, poor scalability, software vulnerabilities of blockchain and scarcity of appropriate incentive mechanisms.
The recent advances in artificial intelligence (AI) have greatly promoted the evolution of conventional computer-aided industry to intelligent industry. The integration of AI with blockchain has the potentials to overcome the limitations of blockchain. For example, machine learning-based approaches may help to analyze the blockchain data and to identify the misbehaviors in blockchain. In addition, deep reinforcement learning methods can be used to improve the reliability of blockchain systems. On the other hand, AI technology heavily depends data availability. For example, deep learning algorithms often require a training process on massive authentic data. However, the data can be falsified, polluted and poisoned thereby disturbing the training model. Thus, it is critical to assure data authentication, provenance and traceability. Blockchain offers a solution to these issues.
There have been substantial developments in blockchain technologies over the last few years. These research outcomes have been extensively reported in journals, conferences and books. Different from most existing books, this book will mainly concentrate on intelligence of blockchain systems. In other words, this book will focus on using AI to improve blockchain systems and blockchain-enabled AI. Areas of this book include (but not limited to), performance optimization of blockchain systems, auto-bug fixing of smart contracts, identifying malicious behaviors in blockchain, applications driven by blockchain intelligence.
This book aims to provide the state-of-the-art research advances in the area of artificial intelligence in blockchain. It presents insights into big data analytics of blockchain data, AI-enabled blockchain systems, and applications driven by blockchain intelligence. This book will be a valuable resource for students, researchers, engineers, policy makers working in various areas related to blockchain intelligence.
Blockchain technology being characterized by decentralization, immutability, non-repudiation and traceability is reshaping the industry while it also poses challenges such as difficulty of data analytics on encrypted data, poor scalability, software vulnerabilities and scarcity of appropriate incentive mechanisms. Meanwhile, recent advances in artificial intelligence have the potentials to overcome the limitations of blockchain. In particular, machine learning approaches can analyse blockchain data and identify the misbehaviours in blockchain. This book provides a comprehensive coverage of up-to-date conceptual frameworks in AI-enabled blockchain systems, automated smart contracts on top of blockchain and applications driven by blockchain intelligence. Different from other existing books, this volume predominately focuses on AI-enabled blockchain systems. Areas covered big data analytics of blockchain data, AI-enabled blockchain systems, and applications driven by blockchain intelligence.
We welcome book chapter contributions on the following (but not limited to) themes.