  Digital technologies have changed the way supply chain operations are
structured. In this article, we conduct systematic syntheses of literature on
the impact of new technologies on supply chains and the related cyber risks. A
taxonomic/cladistic approach is used for the evaluations of progress in the
area of supply chain integration in the Industrial Internet of Things and
Industry 4.0, with a specific focus on the mitigation of cyber risks. An
analytical framework is presented, based on a critical assessment with respect
to issues related to new types of cyber risk and the integration of supply
chains with new technologies. This paper identifies a dynamic and self-adapting
supply chain system supported with Artificial Intelligence and Machine Learning
(AI/ML) and real-time intelligence for predictive cyber risk analytics. The
system is integrated into a cognition engine that enables predictive cyber risk
analytics with real-time intelligence from IoT networks at the edge. This
enhances capacities and assist in the creation of a comprehensive understanding
of the opportunities and threats that arise when edge computing nodes are
deployed, and when AI/ML technologies are migrated to the periphery of IoT
networks.
