IIoT: Traffic Data Flow Analysis and Modeling Experiment for Smart IoT Devices

Abstract

The Internet of Things (IoT) has redefined several aspects of our daily lives, including automation and control of the living environment, innovative healthcare services, and much more. Digital IoT devices and sensors, when integrated with home appliances, industrial systems, and online services in the physical world, have brought intense, disruptive changes in our lives. The industry and home users have widely embraced these ‘things’ on the Internet or IoT. However, the innate, intrinsic repercussions regarding security and data privacy are not evaluated. Security applies to Industrial IoT (IIoT) is in its infancy stage. Techniques from security and privacy research promise to address broad security goals, but attacks continue to emerge in industrial devices. This research explores the vulnerabilities of IIoT ecosystems not just as individual nodes but as the integrated infrastructure of digital and physical systems interacting with the domains. The authors propose a unique threat model framework to analyze the attacks on IIoT application environments. The authors identified sensitive data flows inside the IIoT devices to determine privacy risks at the application level and explored the device exchanges at the physical level. Both these risks lead to insecure ecosystems. The authors also performed a security analysis of physical domains to digital domains.