Securing Remote User Authentication in Industrial Internet of Things

The Industrial Internet of Things (IIoT) enhances the benefit of the Internet of Things (IoT) to a higher level, especially in industries where human error can lead to catastrophic effects. However, security is a major concern in IIoT as hackers can gain access to connected systems, thus potentially subjecting operations to a shutdown. Besides, the outbreak of the COVID-19 pandemic changed the operations style of organizations into a remote work model. Consequently, there has been a significant increase in cyber-attacks leveraging vulnerabilities of IoT devices connected to the Internet. Considering the above factors, we propose a method of remote user authentication combining Photo Response Non-Uniformity (PRNU) with fingerprint bio-metric, which can prevent attacks. PRNU uniquely identifies the scanner, thereby authenticates the device of the user. To prove the effectiveness of PRNU, we collect fingerprint images from various scanners prototyped using Raspberry Pi and evaluate the performance. Our performance evaluation with a set of 10 fingerprint scanners shows promising results. Moreover, our analysis shows that the proposed scheme achieves a classification accuracy of 99%.