Enhancing Industrial IoT Security with AI and Cloud Computing: A Review of Threats and Solutions

Abstract: 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 AIbased 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.