With the rapid development of big data, it is necessary to transfer the
massive data generated by end devices to the cloud under the traditional
cloud computing model. However, the delays caused by massive data
transmission no longer meet the requirements of various real-time mobile
services. Therefore, the emergence of edge computing has been recently
developed as a new computing paradigm that can collect and process data
at the edge of the network, which brings significant convenience to
solving problems such as delay, bandwidth, and off-loading in the
traditional cloud computing paradigm. By extending the functions of the
cloud to the edge of the network, edge computing provides effective data
access control, computation, processing and storage for end devices.
Furthermore, edge computing optimizes the seamless connection from the
cloud to devices, which is considered the foundation for realizing the
interconnection of everything. However, due to the open features of edge
computing, such as content awareness, real-time computing and parallel
processing, the existing problems of privacy in the edge computing
environment have become more prominent. The access to multiple
categories and large numbers of devices in edge computing also creates
new privacy issues.
In this book, we discuss on the research background and current research
process of privacy protection in edge computing. In the first chapter,
the state-of-the-art research of edge computing are reviewed. The second
chapter discusses the data privacy issue and attack models in edge
computing. Three categories of privacy preserving schemes will be
further introduced in the following chapters. Chapter three introduces
the context-aware privacy preserving scheme. Chapter four further
introduces a location-aware differential privacy preserving scheme.
Chapter five presents a new blockchain based decentralized privacy
preserving in edge computing. Chapter six summarize this monograph and
propose future research directions.
In summary, this book introduces the following techniques in edge
computing: 1) describe an MDP-based privacy-preserving model to solve
context-aware data privacy in the hierarchical edge computing paradigm;
2) describe a SDN based clustering methods to solve the location-aware
privacy problems in edge computing; 3) describe a novel blockchain based
decentralized privacy-preserving scheme in edge computing. These
techniques enable the rapid development of privacy-preserving in edge
computing.
