A Survey of Privacy and Security Challenges in Industrial Settings

Abstract

Through interconnecting machines, sensors, and devices, the Industrial Internet of Things (IIoT) has revolutionized industrial processes by allowing real-time data analysis and decision-making. The implementation of cloud, edge, and fog computing models has followed IIoT development, bringing unique security and privacy challenges in their wake. In this all-encompassing report, the potential risks, complications, and apprehensions of these models are analyzed with respect to IIoT integration. Examining cloud, edge, and fog computing models distinguishes and assesses their benefits when applied to IIoT. The paper analyzes the strengths offered by each model and addresses the risks associated with security and privacy, such as data infringement, malware, and denial-ofservice attacks. IIoT systems, in particular, pose significant challenges in providing protection. Cloud, edge, and fog computing models provide ample benefits but IIoT systems utilizing these models must have strong security and privacy policies in place. This paper highlights specific technical and organizational strategies to tackle potential challenges and risks. By effectively implementing these strategies, organizations can tap into the advantages of these models while ensuring the safety of their IIoT systems. Informed decisions can be made, and IIoT deployments can be safeguarded with the aid of the valuable resource given in this paper, which offers comprehensive analysis and recommendations. For those in the field of IIoT security, including practitioners and researchers, this paper is of great value.