Enhancing Industrial IoT Security with AI and Cloud Computing: A Review of Threats and Solutions
S. Saravana Kumar, Balaji Kannan · 2025
Installing and using the Industrial Internet of Things (IIoT) technology at a higher rate has led to enormous changes in the industrial activities and a paradigm shift in the way industries operate, as well as in the manner in which management of assets and supply chain management is done. The digitalisation process allows us to collect data in real-time, have a predictive maintenance, and implement smart automation, which significantly increases operational efficiency and productivity. But this fast transformation has opened the door to a major issue of cybersecurity that poses a risk to integrity, confidentiality, and availability of important industrial infrastructure. An enlargement of networked things and technologies raises the attack surface such that IIoT ecosystems experience a more significant risk of being attacked by OT, like data breaches, ransomware, industrial espionage. The present paper is a detailed account of the key security threats affecting IIoT settings, which is then followed by a detailed analysis of how the features of artificial intelligence (AI) solutions and cloud-based platforms could be used to improve threat detection, incident response, and system resiliency. The combination of an analysis of recent threat vectors, new vulnerabilities, and new defense capabilities allows proposing a framework of best practices in securing IIoT infrastructure, within the study. Although AI-based threat detection and cloud-based security orchestration have become prime technological solutions, the results of further research and optimization are required to establish a workable and scalable implementation of security.