Blockchain Technology for IoT Applications (Blockchain Technologies)

This book explores recent advances in the Internet of things (IoT) via advanced technologies and provides an overview of most aspects which are relevant for advance secure, distributed, decentralized blockchain technology in the Internet of things, their applications, and industry IoT. The book provides an in-depth analysis of the step-by-step evolution of IoT to create a change by enhancing the productivity of industries. It introduces how connected things, data, and their communication (data sharing) environment build a transparent, reliable, secure environment for people, processes, systems, and services with the help of blockchain technology.

Dr. Seok-Won Lee is currently a Full Professor and Chair of Depts. of Software & Computer Engineering and Artificial Intelligence, and Head of Graduate School of Software at Ajou University, South Korea since 2012. He has been a Professor of Information Systems and Cyber Security at the University of Texas at San Antonio, Visiting Professor at the University of Nebraska Lincoln and a Professor of Software Engineering and a Director of Knowledge-intensive Software Engineering (NiSE) research group at the University of North Carolina at Charlotte, USA. Prior to joining to the UNC Charlotte, he was affiliated with Science Applications International Corporation (SAIC) and IBM T.J. Watson Research Center as senior research scientists. He received his M.Sc. in Computer Science (with specialization in Artificial Intelligence) from University of Pittsburgh, and Ph.D. in Software Engineering from George Mason University. His areas of specialization include software engineering with specific expertise in ontological requirements engineering and domain modeling, and knowledge engineering with specific expertise in knowledge acquisition, machine learning and knowledge-based systems. He serves as chairs, organizers, editors and the program committee members for numerous top-tier journals, flagship conferences, and workshops in software engineering, requirements engineering, secure software engineering and other related areas such as information security and assurance, critical infrastructure protection, service-oriented computing, visual analytics and self-adaptive software systems. He has published more than 180 refereed articles and is a senior member of IEEE, ACM and AAAI.

Irish Singh is a PhD researcher at the Department of Computer Engineering at Ajou University, Suwon, South Korea. She completed her M.Tech. degree at the Department of Computer Science and Engineering at Birla Institute of Technology (BIT), Ranchi, and B.Tech. in Computer Science and Engineering at UP (State) Technical University, Lucknow, India. Her research interests include adaptive security, cloud computing, requirements engineering, big data, blockchain technology, and the IoT.

Dr. Masoud Mohammadian is Associate Professor at the University of Canberra, Australia. He graduated with M.S. and Ph.D. degrees from the University of Central Queensland and holds an undergraduate degree from Flinders University, Australia. He has twenty-seven years of academic experience, and he has served as a program committee member and/or Co-Chair of a large number of national and international conferences. He has received awards from the IEEE and the Austrian Ministry of Commerce, as well as several awards for his academic services in Australia. He was a scientific advisor to SolveIT Pty Ltd, and he is currently a scientific advisor to Complexica Pty Ltd. He has delivered a large number of keynote lectures at national and international conferences and has edited 24 books and conference proceedings in the area of computational intelligence and intelligent agents. He has written more than 160 refereed publications, including books, book chapters, journal articles, and conference papers. Dr. Mohammadian’s current research focuses on the application of computational intelligence techniques for learning and adaptation of intelligent agents and web-based information filtering and data mining.