A Practical Analysis of Persuasive and Dark Patterns for IIoT and Industrial Cyber-Physical Systems

Sensors and actuators are essential for monitoring and controlling industrial processes. Both kinds of devices are usually managed through Industrial Internet of Things (IIoT) platforms and Industrial Cyber-Physical Systems (ICPS), whose cybersecurity is critical. This paper focuses on such cybersecurity by analyzing how a set of attacks known as Persuasive and Dark Patterns can affect user interaction with IIoT applications and ICPSs. By capturing data on how users interact with the system's interface elements, valuable insights are gained into the operator behavior within the industrial environment. Specifically, two versions of the same application are compared: one incorporating Dark Patterns and another one that makes use of Persuasive Patterns. The obtained results reveal significant differences in user behavior, highlighting the impact on user experience and navigation efficiency in an industrial scenario.