This book aims to sort out the clear logic of the development of machine learning-driven privacy preservation in IoTs, including the advantages and disadvantages, as well as the future directions in this under-explored domain. In big data era, an increasingly massive volume of data is generated and transmitted in Internet of Things (IoTs), which poses great threats to privacy protection. Motivated by this, an emerging research topic, machine learning-driven privacy preservation, is fast booming to address various and diverse demands of IoTs. However, there is no existing literature...

In the process of transforming modern manufacturing into intelligent manufacturing, more and more manufacturing processes are being deployed digitally on the Internet. As a novel digital industrial infrastructure and new application ecology, Industrial Internet could integrate the novel information and communication technology into various industrial manufacturing processes, through the safe and reliable intelligent interconnection of factors concerning people, machines and things. It aims at significantly improving the digitalization, networking and intelligence of manufacturing processes...