Toward Data Security in Edge Intelligent IIoT

Abstract

IIoT significantly improves industrial productivity and at the same time reduces manufacturing costs. In order to satisfy the requirements in IIoT applications, such as location awareness and low latency, edge intelligence has been proposed to enhance the capability of processing data at the edge of the network. As a typical example of edge intelligence, fog computing offers a lot of potential benefits including transient storage, decentralized computation, stronger security, and so on. In this article, we mainly focus on the data security in edge intelligent IIoT. We present four major challenges in data security of edge intelligent IIoT, including reliable storage, convenient usage, efficient search, and secure deletion, and provide the corresponding solutions to each challenge. Furthermore, we propose an optimized framework, which enjoys higher security and better integration to IIoT. The proposed framework promotes the underlying IIoT in data acquisition, processing, and transition, thus leading to stronger security and better efficiency. Finally, we implement the solutions on a desktop and Raspberry Pi, and demonstrate the experimental results.