An overview of privacy preserving schemes for industrial Internet of Things
Yan Huo, Chun Meng, Ruinian Li, Tao Jing
Abstract
The concept of Internet of Everything is like a revolutionary storm, bringing the whole society closer together. Internet of Things (IoT) has played a vital role in the process. With the rise of the concept of Industry 4.0, intelligent transformation is taking place in the industrial field. As a new concept, an industrial IoT system has also attracted the attention of industry and academia. In an actual industrial scenario, a large number of devices will generate numerous industrial datasets. The computing efficiency of an industrial IoT system is greatly improved with the help of using either cloud computing or edge computing. However, privacy issues may seriously harmed interests of users. In this article, we summarize privacy issues in a cloud- or an edge-based industrial IoT system. The privacy analysis includes data privacy, location privacy, query and identity privacy. In addition, we also review privacy solutions when applying software defined network and blockchain under the above two systems. Next, we analyze the computational complexity and privacy protection performance of these solutions. Finally, we discuss open issues to facilitate further studies.