In recent years, the fast-paced development of social information and networks has led to the explosive growth of data. A variety of big data have emerged, encouraging researchers to make business decisions by analysing this data. However, many challenges remain, especially concerning data security and privacy. Big data security and privacy threats permeate every link of the big data industry chain, such as data production, collection, processing, and sharing, and the causes of risk are complex and interwoven. Blockchain technology has been highly praised and recognised for its decentralised infrastructure, anonymity, security, and other characteristics, and it will change the way we access and share information. In this book, the author demonstrates how blockchain technology can overcome some limitations in big data technology and can promote the development of big data while also helping to overcome security and privacy challenges. The author investigates research into and the application of blockchain technology in the field of big data and assesses the attendant advantages and challenges while discussing the possible future directions of the convergence of blockchain and big data. After mastering concepts and technologies introduced in this work, readers will be able to understand the technical evolution, similarities, and differences between blockchain and big data technology, allowing them to further apply it in their development and research. Author: Shaoliang Peng is the Executive Director and Professor of the College of Computer Science and Electronic Engineering, National Supercomputing Centre of Hunan University, Changsha, China. His research interests are high-performance computing, bioinformatics, big data, AI, and blockchain.

In recent years, the fast-paced development of social information and networks has led to the explosive growth of data. A variety of big data have emerged, encouraging researchers to make business decisions by analysing this data. However, many challenges remain, especially concerning data security and privacy. Big data security and privacy threats permeate every link of the big data industry chain, such as data production, collection, processing, and sharing, and the causes of risk are complex and interwoven. Blockchain technology has been highly praised and recognised for its decentralised infrastructure, anonymity, security, and other characteristics, and it will change the way we access and share information. In this book, the author demonstrates how blockchain technology can overcome some limitations in big data technology and can promote the development of big data while also helping to overcome security and privacy challenges. The author investigates research into and the application of blockchain technology in the field of big data and assesses the attendant advantages and challenges while discussing the possible future directions of the convergence of blockchain and big data. After mastering concepts and technologies introduced in this work, readers will be able to understand the technical evolution, similarities, and differences between blockchain and big data technology, allowing them to further apply it in their development and research. Author: Shaoliang Peng is the Executive Director and Professor of the College of Computer Science and Electronic Engineering, National Supercomputing Centre of Hunan University, Changsha, China. His research interests are high-performance computing, bioinformatics, big data, AI, and blockchain.

This two volume set (CCIS 623 and 634) constitutes the refereed proceedings of the Second International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, held in Harbin, China, in August 2016. The 91 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers are organized in topical sections on Research Track (Part I) and Education Track, Industry Track, and Demo Track (Part II) and cover a wide range of topics related to social computing, social media, social network analysis, social modeling, social recommendation, machine learning, data mining.

This two volume set (CCIS 623 and 634) constitutes the refereed proceedings of the Second International Conference of Young Computer Scientists, Engineers and Educators, ICYCSEE 2016, held in Harbin, China, in August 2016. The 91 revised full papers presented were carefully reviewed and selected from 338 submissions. The papers are organized in topical sections on Research Track (Part I) and Education Track, Industry Track, and Demo Track (Part II) and cover a wide range of topics related to social computing, social media, social network analysis, social modeling, social recommendation, machine learning, data mining.